#speech-to-text api 2020

[learnwithearn]

The Rise of AI: Transforming Businesses and Redefining the Future

The world of Artificial Intelligence (AI) is booming. Forget the hype – businesses are actively integrating AI technologies, with startups and tech giants vying for a piece of the action. Investment is soaring, and companies are rapidly adopting AI solutions to gain a competitive edge.

A recent survey by Narrative Science revealed that nearly 40% of companies were already leveraging AI in 2017, with that number projected to skyrocket to over 60% by 2018. Forrester Research echoes this sentiment, predicting a staggering 300% increase in AI investment compared to the previous year. The International Data Corporation (IDC) estimates the AI market to balloon from nearly €8 billion in 2016 to a staggering €47 billion by 2020.

This surge is fueled by the vast potential of AI technologies. What began in 1955 as a subfield of computer science has blossomed into a diverse landscape of tools and techniques, both recent and well-established.

Unveiling the Top 10 AI Technologies

To shed light on the power of AI, let's explore the top 10 AI technologies identified by Forrester Research in their TechRadar report, a valuable resource for application development professionals:

Automatic Text Generation: Imagine computers generating insightful reports, summarizing complex data, and crafting compelling content. This technology is already transforming customer service interactions and business intelligence practices. (Examples: Attivio, Narrative Science, SAS)

Automatic Speech Recognition: Ever wished your phone could flawlessly transcribe your voice messages? Speech recognition technology makes it possible, paving the way for advanced voice-driven applications and interactive systems. (Examples: Nuance Communications, Open Text)

Virtual Agents: From basic chatbots to sophisticated virtual assistants, these AI-powered companions are capturing media attention. They're already revolutionizing customer service and even managing smart homes. (Examples: Amazon, Google, IBM, Microsoft)

Machine Learning Platforms: Think of these platforms as AI training grounds. They provide the algorithms, APIs, tools, and computing power needed to design, train, and deploy AI models across applications, processes, and machines. (Examples: Amazon, Google, Microsoft, SAS)

AI-Optimized Hardware: Unleashing the full potential of AI requires specialized hardware. Enter AI-optimized processors and devices, designed to run demanding AI computations efficiently. (Examples: Google, IBM, Nvidia)

The remaining sections will be presented in the same format, with headings and brief descriptions of each technology.

Decision Support

Deep Learning

Biometric Recognition

Robotic Process Automation

AI can analyze and understand written language through text mining and NLP

Conclusion

While AI offers a treasure trove of benefits for businesses, a 2016 Forrester survey revealed some hurdles hindering wider adoption. Companies grapple with defining a clear business case, understanding the true value of AI, and acquiring the necessary skills. Data management infrastructure modernization and budget limitations also pose challenges. Despite these obstacles, Forrester concludes that overcoming them unlocks the power of AI to transform customer-facing applications and create a seamlessly interconnected network of business intelligence.

[brillmind]

How much would it cost to develop an app like Amazon Alexa

Voice aides have turned into a significant piece of regular daily existence for some individuals. It has started overtaking traditional internet search. On the off chance that individuals need to find any data, they basically shoot a voice order and get list items in the blink of an eye. This degree of comfort is drawing in individuals to attempt voice collaborator applications like Siri, Alexa, Google Colleague, and so on. According to the survey, voice searches will account for 50% of all searches by 2020. Organizations are putting resources into voice aide application advancement to further develop client experience

What is voice assistant app

By and large, a voice assistant application answers voice orders and gives clients exact data about their inquiries. With the assistance of such applications, it turns out to be not difficult to handle requests of items, perform activities like playing music, switch on/off the lights, or calling a companion.

Also Read More: Game development  company in Bangalore

What technologies are used in Mobile Assistants?

Speech to text (STT) engine: In this, the user’s voice is converted into text. The voice might be of clients or any arbitrary brief snippet.

Text to discourse (TTS) motor: This motor can change text over completely to discourse, and it is exceptionally helpful when the client is involved in another work.

Tagging: With this, the voice partner can comprehend what the client is attempting to say.

Sound decrease engine: This motor guides in offsetting the outside climate commotion. If not, there will be an excessive number of improvements that an application should process.

Voice biometrics: This confirmation interaction helps an application to comprehend that it is especially your voice.

UI: it involves two sections, the voice, and the call out. Users can hear the answers to their questions in the voice part, and callouts are where they can see the results on the screen.

Speech compression motor: This can pack the voice of the clients so it can arrive at the server quicker.

Also Read More: Rummy Game Development company in India

How to make a voice partner application like Alexa

There are mainly three methods that mobile app development companies deploy for building a voice assistant app- Junior method, which involves the integration of voice assistant technology to a mobile app using APIs. You can likewise attempt the center strategy, where you can fabricate a voice right hand utilizing open source administrations and APIs.

Junior method

This technique includes the combination of confided in innovation inside a current application. For this purpose, you need to get a kit and then integrate it within an app. The unit is utilized to characterize the plans as kinds of solicitations, and afterward explains the sorts and you need to bunch it into spaces. This is the way the lesser strategy works.

Middle method

This technique is reasonable for the people who know about AI. In addition to web and mobile services, you can develop an AI assistant app with a few tools:

Melissa: An incredible device for those are new to building voice colleague applications. It has the capacity of talking, taking notes, and perusing the news.

Jasper: A famous open-source stage is utilized for making voice-controlled applications. This device can tune in and learn. The great part is that it can follow clients' propensities quietly and gives you exact data on time.

Api.ai: It provides a complete range of features for making virtual assistant app development simpler. Alongside that, it upholds voice-to-message transformation with the execution of an important arrangement of undertakings.

Senior method

This technique is suggested for no-nonsense engineers who have related knowledge in creating AI applications without any preparation.

Google's Tensorflow: This open-source programming library has an adaptable construction. It tends to be utilized on various servers, cell phones, and so forth. You can use it easily as it is flexible and portable.

Also Read More: Ludo Game Development company in bangalore

How much does voice assistant app development cost?

The improvement cost relies upon the intricacy and the quantity of highlights that you need to add in your application. For building an app like Alexa, it would cost around $15,000-$50,000.

Protected to specify voice collaborator applications like Alexa have turned into a fundamental piece of our everyday lives. It is used in different circles from medical services to coordinated factors and organizations are making the most out of it. Although it may appear simple to replicate an idea for a voice assistant application, developing something entirely new is a challenging process. On the off chance that you follow the above-framed advances, it would be feasible to construct an application like Alexa.

[hellomarnieserranoworld]

The massive growth in cloud-based technologies is taking the Speech-to-Text API market by storm

[mariacallous]

In the weeks following the release of OpenAI’s viral chatbot ChatGPT late last year, Google AI chief Jeff Dean expressed concern that deploying a conversational search engine too quickly might pose a reputational risk for Alphabet. But last week Google announced its own chatbot, Bard, which in its first demo made a factual error about the James Webb Space Telescope.

Also last week, Microsoft integrated ChatGPT-based technology into Bing search results. Sarah Bird, Microsoft’s head of responsible AI, acknowledged that the bot could still “hallucinate” untrue information but said the technology had been made more reliable. In the days that followed, Bing claimed that running was invented in the 1700s and tried to convince one user that the year is 2022.

Alex Hanna sees a familiar pattern in these events—financial incentives to rapidly commercialize AI outweighing concerns about safety or ethics. There isn’t much money in responsibility or safety, but there’s plenty in overhyping the technology, says Hanna, who previously worked on Google’s Ethical AI team and is now head of research at nonprofit Distributed AI Research.

The race to make large language models—AI systems trained on massive amounts of data from the web to work with text—and the movement to make ethics a core part of the AI design process began around the same time. In 2018, Google launched the language model BERT, and before long Meta, Microsoft, and Nvidia had released similar projects based on the AI that is now part of Google search results. Also in 2018, Google adopted AI ethics principles said to limit future projects. Since then, researchers have warned that large language models carry heightened ethical risks and can spew or even intensify toxic, hateful speech. These models are also predisposed to making things up.

As startups and tech giants have attempted to build competitors to ChatGPT, some in the industry wonder whether the bot has shifted perceptions for when it’s acceptable or ethical to deploy AI powerful enough to generate realistic text and images.

OpenAI’s process for releasing models has changed in the past few years. Executives said the text generator GPT-2 was released in stages over months in 2019 due to fear of misuse and its impact on society (that strategy was criticized by some as a  publicity stunt). In 2020, the training process for its more powerful successor, GPT-3, was well documented in public, but less than two months later OpenAI began commercializing the technology through an API for developers. By November 2022, the ChatGPT release process included no technical paper or research publication, only a blog post, a demo, and soon a subscription plan.

Irene Solaiman, policy director at open source AI startup Hugging Face, believes outside pressure can help hold AI systems like ChatGPT to account. She is working with people in academia and industry to create ways for nonexperts to perform tests on text and image generators to evaluate bias and other problems. If outsiders can probe AI systems, companies will no longer have an excuse to avoid testing for things like skewed outputs or climate impacts, says Solaiman, who previously worked at OpenAI on reducing the system’s toxicity. 

Each evaluation is a window into an AI model, Solaiman says, not a perfect readout of how it will always perform. But she hopes to make it possible to identify and stop harms that AI can cause because alarming cases have already arisen, including players of the game AI Dungeon using GPT-3 to generate text describing sex scenes involving children. “That’s an extreme case of what we can’t afford to let happen,” Solaiman says.

Solaiman’s latest research at Hugging Face found that major tech companies have taken an increasingly closed approach to the generative models they released from 2018 to 2022. That trend accelerated with Alphabet’s AI teams at Google and DeepMind, and more widely across companies working on AI after the staged release of GPT-2. Companies that guard their breakthroughs as trade secrets can also make the forefront of AI less accessible for marginalized researchers with few resources, Solaiman says.

As more money gets shoveled into large language models, closed releases are reversing the trend seen throughout the history of the field of natural language processing. Researchers have traditionally shared details about training data sets, parameter weights, and code to promote reproducibility of results. “We have increasingly little knowledge about what database systems were trained on or how they were evaluated, especially for the most powerful systems being released as products,” says Alex Tamkin, a Stanford University PhD student whose work focuses on large language models.

He credits people in the field of AI ethics with raising public consciousness about why it’s dangerous to move fast and break things when technology is deployed to billions of people. Without that work in recent years, things could be a lot worse.

In fall 2020, Tamkin co-led a symposium with OpenAI’s policy director, Miles Brundage, about the societal impact of large language models. The interdisciplinary group emphasized the need for industry leaders to set ethical standards and take steps like running bias evaluations before deployment and avoiding certain use cases.

Tamkin believes external AI auditing services need to grow alongside the companies building on AI because internal evaluations tend to fall short. He believes participatory methods of evaluation that include community members and other stakeholders have great potential to increase democratic participation in the creation of AI models.

Merve Hickok, who is a research director at an AI ethics and policy center at the University of Michigan, says trying to get companies to put aside or puncture AI hype, regulate themselves, and adopt ethics principles isn’t enough. Protecting human rights means moving past conversations about what’s ethical and into conversations about what’s legal, she says.

Hickok and Hanna of DAIR are both watching the European Union finalize its AI Act this year to see how it treats models that generate text and imagery. Hickok said she’s especially interested in seeing how European lawmakers treat liability for harm involving models created by companies like Google, Microsoft, and OpenAI.

“Some things need to be mandated because we have seen over and over again that if not mandated, these companies continue to break things and continue to push for profit over rights, and profit over communities,” Hickok says.

While policy gets hashed out in Brussels, the stakes remain high. A day after the Bard demo mistake, a drop in Alphabet’s stock price shaved about $100 billion in market cap. “It’s the first time I’ve seen this destruction of wealth because of a large language model error on that scale,” says Hanna. She is not optimistic this will convince the company to slow its rush to launch, however. “My guess is that it’s not really going to be a cautionary tale.”

[aianalytics]

Natural Language Processing: A breakthrough technology in healthcare

Have you ever tried to converse with a computer in the language you speak?

Sounds like a fascinating concept? Well, it is! Lately, there have been noteworthy discoveries in engaging computers to comprehend the language similarly as we do, well known as Natural Language Processing. However, It is anything but a simple errand training machines to see how we, humans convey.

What is Natural Language Processing?

Natural Language Processing, popularly known as NLP, is the field of Artificial Intelligence which gives the computers the ability to understand, read, analyze and interpret the human language. Simply put, it is the relation between the computers and human language. It has several sub-disciplines, including Natural Language Understanding (NLU), Natural Language Generation (NLG), and Natural Language Query (NLQ). Combining the intensity of Artificial Intelligence, computational phonetics, and computer science, NLP permits a machine to comprehend human language which only humans could possibly do, until now. It is viewed as a difficult issue in computer science due to the nature of human language, which makes it troublesome.

The global market size of NLP is growing at a CAGR of 18.6% for period of 2020-2026 and by 2026, it is estimated to reach to USD 27.6 Billion, from USD 9.9 Billion in 2020. The NLP market consists of major growth factors like the increase in smart device usage, growth in the adoption of cloud-based solutions and NLP-based applications to improve customer service, as well as the increase in technological investments in the healthcare industry.

NLP in Healthcare Natural Language Processing is rapidly being adopted in Healthcare industry. It has realized the potential of this cutting edge technology in streamlining the processes. Healthcare industry is quick in understanding the significance of information, gathering data from EMRs/EHRs and other sources. Huge volumes of unstructured patient data is inputted into EHRs on a daily basis, but it’s hard for a computer to help physicians aggregate that critical data. Structured data like claims or CCDAs / FHIR APIs may help determine disease burden, but gives us a limited view of the actual patient record. With the fragmented nature of the healthcare industry, large amount of data is collected in silos having as much as 80 percent of data unstructured and of poor quality. This brings us to a pertinent challenge of data extraction and utilization in the healthcare space through NLP in Healthcare. This unstructured data will take a lot of time and effort if humans try to structure it manually, making the data unusable. This hinders us from taking effective decisions through analytics because of the form of our data. Therefore, NLP can help to leverage this unstructured data as we make a shift gradually from fee for service model to value based care. For healthcare and life sciences, by 2025 the global market size of NLP is assessed to reach USD 3.7 billion from current size in 2020 that is USD 1.5 billion. Also, it is growing at CAGR of 20.5%. The healthcare and life sciences NLP market include the factors such as increasing use of predictive analytics to enhance health outcomes and growing demand for improving Electronic Health Record (EHR) data usability to enhance patient care. The worldwide healthcare and life sciences NLP market consists of important vendors such as the vendors from United States of America include 3M, Lexalytics, AWS, Google, Nuance, Microsoft, IBM and others. Clinithink is a vendor from Georgia. From Germany, Averbis is a major vendor. Linguamatics is a vendor from the United Kingdom.  Use Cases Primarily, this technology is helping the healthcare in the following ways 1.      Comprehending human speech and extracting its meaning 2.      Unlocking unstructured data in databases and documents by mapping out essential concepts and values and allowing physicians to use this information for decision making and analytics Likewise, some of the Use cases in healthcare can be broadly highlighted in the following 3 groups: 1.      Mainstay Use Cases for NLP which has a proven ROI A.     Speech Recognition: NLP allows the transcription of huge amount of clinical notes from speech to text. This reduces the task of physicians to dictate notes and therefore, saves time by avoiding duplication. Many companies are working in medical transcription space like Acusis, SmartMD, IKS Health, Aquity and many more B.     Clinical Documentation: NLP helps the physicians freeing up from the manual and complex structure of EMRs allowing them to focus more on patient care. Nuance and M*Modal have technologies that work in tandem with their speech recognition technologies to capture structured data at the point of care and standardized terminologies for future use In the future, NLP tools could be applied to social media and other public data sets to determine social determinants of health (SDOH) as well as the effectiveness of wellness-based programs and initiatives. C.     Computer Assisted Coding (CAC): Computer-assisted coding extracts information about procedures and therapies to capture every code and maximize claims D.     Data Mining: NLP helps to mine the unstructured patient data allowing organizations to reduce the levels of subjectivity in decision-making and improve the quality of patient care 2.      Emerging Use cases of NLP A.     Clinical Trial matching: Using NLP and machine learning in healthcare to identify patients for a clinical trial with the help of NLP engines for trial matching B.    Pharmacovigilance: IQVIA is trying to apply machine learning with natural language processing to transform many Pharmacovigilance functions for greater accuracy and speed [10] C.     Prior Authorization: NLP modules can be used by Payer to determine prior authorization rapidly. Companies like IBM Watson and Anthem are working on these NLP modules D.     Clinical Decision Support (CDS): CDS help physicians to make better decisions. Also, it is being used to aid clinicians in checking symptoms and diagnosis E.      Risk Adjustment and Hierarchical Condition Categories (HCC): HCC relies on ICD-10 coding to assign risk scores to each patient. NLP can help assign patients a risk factor and use their score to predict the costs of healthcare 3.      Next gen Use cases of NLP A.     Ambient Virtual Scribe: NLP can be used to develop a speech recognition software for clinical documentation giving rise to Virtual scribes limiting the need for human scribes B.    Precision Medicine: NLP can be used for Computational Phenotyping and Biomarker Discovery C.     Population Surveillance: An application of NLP to EMRs can be identifying a subset of an ethnic or racial group for eventually documenting and mapping health disparities

Challenges A key challenge in widespread application of NLP is adapting existing systems to new clinical settings

The Future

NLP technologies finds its applications for a range of purposes in Healthcare and Research, including Clinical documentation, medical transcription, clinical trials, Decision Support System and many more. However, the real-life implementation is still facing obstacles. Even though, NLP has the potential to revolutionize with their breakthrough technology and change the landscape of healthcare industry. It is creating new and exciting opportunities in healthcare delivery and patient experience. Natural Language Processing is here to stay, a technology that gets smarter with time, as it empowers the providers to positively influence the health outcomes.

[thehierophage]

Holy Day Meditation for April 7, 2020 æ.v.

April 7, 2020 æ.v. Dies Martis, Sol 18° Aries, Luna 9° Libra An Vvi æ.n.

Do what thou wilt shall be the whole of the Law.

The Day of Daleth, the Day of the Empress

Hebrew Letter: Daleth

Numerical Value as Letter: 4

Numerical Value as Word: 434 (Daleth+Lamed+Tav)

Meaning: A Door.

Thoth Card: The Empress (Atu III)

Alternate Title: The Daughter of the Mighty Ones.

Image:

Correspondences:

Tree of Life Path Association: Key 14 - Binah to Chokmah (from Sephira 3-2)

Astrological Sign: Venus

Element: -

Egyptian Godforms: Hathoor

Geomantic Figure: Heptagram

Gemstones: Emerald, Turquoise

Perfumes: Sandalwood, Myrtle, all Soft Voluptuous Odors

Plants: Myrtle, Rose, Clover, Fig, Peach, Apple

Animals: Sparrow, Dove, Sow

Colors:

King Scale – Emerald green

Queen Scale – Sky blue

Prince Scale – Early spring green

Princess Scale – Bright rose of cerise rayed pale yellow

The Secret Instruction of the Master:

This is the Harmony of the Universe, that Love unites the Will to create with the Understanding of that Creation: understand thou thine own Will! Love and let love! Rejoice in every shape of love, and get thy rapture and thy nourishment thereof!

Mnemonic:

Beauty, display thine Empire! Truth above

Thought's reach: the wholeness of the world is Love.

Liber Arcanorum Verse

3. The Virgin of God is enthroned upon an oyster-shell; she is like a pearl, and seeketh Seventy to her Four. In her heart is Hadit the invisible glory.

Genius of the House of Mercury

DhnaⲜartarωθ

Genius of the Prison of the Qliphoth

Dagadgiel

Recommended Text for Meditation:

Liber VII Liberi vel Lapis Lazuli, Cap. 7

Liber VII Liberi vel Lapis Lazuli

Being the Voluntary Emancipation of a certain Exempt Adept from his Adeptship. These are the Birth-Words of a Master of the Temple. A.˙. A.˙. Publication in Class A. Imprimatur: N. Fra A.˙. A.˙.

VII

1. By the burning of the incense was the Word revealed, and by the distant drug.

2. O meal and honey and oil! O beautiful flag of the moon, that she hangs out in the centre of bliss!

3. These loosen the swathings of the corpse; these unbind the feet of Osiris, so that the flaming God may rage through the firmament with his fantastic spear.

4. But of pure black marble is the sorry statue, and the changeless pain of the eyes is bitter to the blind.

5. We understand the rapture of that shaken marble, torn by the throes of the crowned child, the golden rod of the golden God.

6. We know why all is hidden in the stone, within the coffin, within the mighty sepulchre, and we too answer Olalam! Imal! Tutulu! as it is written in the ancient book.

7. Three words of that book are as life to a new aeon; no god has read the whole.

8. But thou and I, O God, have written it page by page.

9. Ours is the elevenfold reading of the Elevenfold word.

10. These seven letters together make seven diverse words; each word is divine, and seven sentences are hidden therein.

11. Thou art the Word, O my darling, my lord, my master!

12. O come to me, mix the fire and the water, all shall dissolve.

13. I await Thee in sleeping, in waking. I invoke Thee no more; for Thou art in me, O Thou who hast made me a beautiful instrument tuned to Thy rapture.

14. Yet art Thou ever apart, even as I.

15. I remember a certain holy day in the dusk of the year, in the dusk of the Equinox of Osiris, when first I beheld Thee visibly; when first the dreadful issue was fought out; when the Ibis-headed One charmed away the strife.

16. I remember Thy first kiss, even as a maiden should. Nor in the dark byways was there another: Thy kisses abide.

17. There is none other beside Thee in the whole Universe of Love.

18. My God, I love Thee, O Thou goat with gilded horns!

19. Thou beautiful bull of Apis! Thou beautiful serpent of Apep! Thou beautiful child of the Pregnant Goddess!

20. Thou hast stirred in Thy sleep, O ancient sorrow of years! Thou hast raised Thine head to strike, and all is dissolved into the Abyss of Glory.

21. An end to the letters of the words! An end to the sevenfold speech.

22. Resolve me the wonder of it all into the figure of a gaunt swift camel striding over the sand.

23. Lonely is he, and abominable; yet hath he gained the crown.

24. Oh rejoice! rejoice!

25. My God! O my God! I am but a speck in the star-dust of ages; I am the Master of the Secret of Things.

26. I am the Revealer and the Preparer. Mine is the Sword - and the Mitre and the Winged Wand!

27. I am the Initiator and the Destroyer. Mine is the Globe - and the Bennu bird and the Lotus of Isis my daughter!

28. I am the One beyond these all; and I bear the symbols of the mighty darkness.

29. There shall be a sigil as of a vast black brooding ocean of death and the central blaze of darkness, radiating its night upon all.

30. It shall swallow up that lesser darkness.

31. But in that profound who shall answer: What is?

32. Not I.

33. Not Thou, O God!

34. Come, let us no more reason together; let us enjoy! Let us be ourselves, silent, unique, apart.

35. O lonely woods of the world! In what recesses will ye hide our love?

36. The forest of the spears of the Most High is called Night, and Hades, and the Day of Wrath; but I am His captain, and I bear His cup.

37. Fear me not with my spearmen! They shall slay the demons with their petty prongs. Ye shall be free.

38. Ah, slaves! ye will not - ye know not how to will.

39. Yet the music of my spears shall be a song of freedom.

40. A great bird shall sweep from the abyss of Joy, and bear ye away to be my cup-bearers.

41. Come, O my God, in one last rapture let us attain to the Union with the Many!

42. In the silence of Things, in the Night of Forces, beyond the accursed domain of the Three, let us enjoy our love!

43. My darling! My darling! away, away beyond the Assembly and the Law and the Enlightenment unto an Anarchy of solitude and Darkness!

44. For even thus must we veil the brilliance of our Self.

45. My darling! My darling!

46. O my God, but the love in Me bursts over the bonds of Space and Time; my love is spilt among them that love not love.

47. My wine is poured out for them that never tasted wine.

48. The fumes thereof shall intoxicate them and the vigour of my love shall breed mighty children from their maidens.

49. Yea! without draught, without embrace: - and the Voice answered Yea! these things shall be.

50. Then I sought a Word for Myself; nay, for myself.

51. And the Word came: O Thou! it is well. Heed naught! I love Thee! I love Thee!

52. Therefore had I faith unto the end of all; yea, unto the end of all.

Love is the law, love under will.

[gerzah]

Neuer Blogpost: Wie man die aktuelle Ausgabe der c’t als Hörbuch konsumiert

Wer mit öffentlichen Verkehrsmitteln zur Arbeit pendelt und dabei die Computerzeitschrift c’t lesen möchte, hat mit der passenden App eine gute Möglichkeit, diese am Handy oder Tablet zu konsumieren. Sitzt man aber am Steuer des eigenen PKWs, sollte es schon eine gesprochene Fassung sein; eine solche gibt es aber bislang nicht. Mit etwas Handarbeit und „Text to Speech“-Vorlesefunktion (TTS) funktioniert dies mit einem Android-Handy sogar ohne permanente Internetverbindung recht gut. — Nachfolgend findet sich meine Lösung zum Nachmachen.

Der Start: Das Digital-Abo der c’t

Den Start bildet ein Digital-Abo der c’t. Um herauszufinden, ob man so etwas hat, schaut am besten unter shop.heise.de unter „Abo“ nach. Lässt sich die aktuelle c’t dort als PDF-Datei (mit persönlichem Watermark) herunterladen, hat man das passende Abo. — Nebenbei bemerkt: Ich gehe davon aus, dass die nachfolgende Vorgehensweise auch mit den Schwester-Zeitschriften der c’t des Heise-Verlags funktioniert, also iX, Mac & i, Technology Review und Make.

Die heruntergeladene PDF-Datei ist eigentlich bereits eine gute Basis für die Vorlesefunktion. Die Erfahrung zeigt aber, dass beim mehrspaltigen PDF-Print-Layout mitunter unpassende Vorlese-Reihenfolgen entstehen, und dass sporadisch mal Kopf- oder Fußzeilen mitten im Text erneut zu Gehör gebracht werden – das ist natürlich unschön.

Idealer Einstieg: Heise Select

Den besseren Einstieg bietet die Online-Ausgabe der c’t unter „Heise Select“. Hier lassen sich alle redaktionellen Bestandteile der aktuellen Ausgabe in sauber formatierter HML-Fassung direkt im Browser lesen. — Obacht: Bitte stichprobenartig überprüfen, ob man hier tatsächlich tatsächlich angemeldet ist und die Volltexte sehen kann, siehe Screenshots.

Ist das tatsächlich der Fall, sind alle Vorbedingungen erfüllt, um den redaktionellen Teil in Form einzelner HTML-Dateien pro Artikel auf den eigenen Computer herunterzuladen, die für die Vorleser-App deutlich besser zu verdauen sind als die im Print-Layout formatierte, monolithische PDF-Datei. Allerdings wird man schwerlich jeden einzelnen Artikel mit der rechten Maustaste anklicken und so deren HTML-Fassungen einzeln auf die Festplatte speichern wollen.

Kekse für wget

Daher geht es nun in die Kommandozeile – das ist ein bisschen nerdig, aber hey, wir reden hier ja von der c’t und nicht von einer Modezeitschrift. Also: Ein bisschen Einsatz bitte!

Gefragt ist das kostenlos verfügbare Open Source-Kommandozeilen-Tool „wget“, das alle HTML-Dateien in einem Rutsch ohne fehlerträchtige Handarbeit bequem auf den eigen Computer herunterlädt. Ist wget auf dem jeweiligen Computer noch nicht vorhanden, lässt es sich unter Linux meist recht einfach per Paketmanager nachrüsten, am Mac empfehle ich dem geneigten Nerd den Weg über Homebrew. Für Windows findet man wget z.B. unter diesem Link.

wget stellt einen „Browser ohne Fenster“ dar, lädt die besuchten HTML-Dateien herunter und folgt den darin enthaltenen Links, um sicher zu gehen, keine Datei zu vergessen. Korrekt konfiguriert kann man auf diese Weise einen entsprechenden Teil des WWW auf den eigenen Computer kopieren, auch „mirrorn“ genannt.

Würde man wget nun allerdings ohne Vorbereitung auf Heise Select loslassen, würde man nur die gekürzten Ausgaben („Sie wollen wissen, wie es weitergeht?“, s.o.) mit dem Login-Hinweis herunterladen. Das ist nur allzu verständlich, schließlich verfügt wget nicht über die Anmelde-Cookies, mit denen der Heise-Webserver dem Desktop-Browser den Zugriff auf die Volltexte gewährt.

Folglich müssen wir das Cookie-Jar des Desktop-Browsers nach wget transplantieren. Dabei hilft den Nutzern von Google Chrome die Browser-Erweiterung „cookies.txt“.

Sie dient exakt dazu, das komplette, zum aktuellen Download-Pfad gehörige Cookie-Jar in einer .txt-Datei zu speichern, die wget verdauen kann. Anschließend erhält wget dieselben Download-Befugnisse wie das ursprüngliche Browserfenster.

wget – übernehmen Sie!

Meine eigenen Cookies von heise.de habe ich in einer Datei namens „cookies-gero.txt“ gespeichert, die Namensgebung ist natürlich vollkommen beliebig. Derart gewappnet geht’s nun endlich an den Download. Meine Kommandozeile lautet am Beispiel der am 29. Februar 2020 erschienen Ausgabe 06/2020 (in einer Zeile!):

wget -r -l 1 -k -E -p -np -R jpg,jpeg,png,gif,pdf,css,js,svg --cut-dirs=2 --load-cookies cookies-gero.txt https://www.heise.de/select/ct/2020/6/

Im Klartext (vgl. Manpage zu wget): Wir laden rekursiv, folgen also den Links; wir bleiben aber bei einer Link-Tiefe von 1; wir konvertieren Links, wir passen die Endungen an; wir laden Inline-Bilder herunter; wir verbieten das Parent-Directory; wir interessieren uns aber nicht für Bilder und andere Downloads; die ersten beiden Dateinamens-Ebenen der URL sollen beim Speichern aus dem Dateipfad abgeschnitten werden, damit es auf der heimischen Festplatte etwas übersichtlicher bleibt; dann wird noch das aus Chrome heruntergeladene Cookie-Jar eingebunden. Und endlich geht es ab dafür – mit der zur aktuellen Ausgabe passenden URL.

Bei mir dauert der komplette Download der 70-80 Einzeldateien meist ca. 3 Minuten – wobei sicher nicht der Breitband-Anschluss den Flaschenhals darstellt, sondern das Herumsuchen und der Einzel-Download verschiedenen Dateien. Das Resultat ist lediglich ca. 4 MB klein und ist im nachfolgenden Bild dargestellt.

Man wird sporadisch überprüfen wollen, ob die Downloads tatsächlich den vollständigen Text enthalten: Die Anmelde-Cookies haben eine Verfallsdatum, anschließend grast wget das Heise Select-Portal wieder ohne gültige Benutzeranmeldung ab. In diesem Fall muss man sich erneut im Chrome auf der Webseite anmelden und die cookies.txt-Datei erneuern, damit es wieder klappt.

Dateitransfer aufs Handy

Nun transferiert man den Stapel HTML-Dateien an eine geeignet erscheinende Stelle aufs Android-Handy. Jeder mag hier die eigene präferierte Methode verwenden: Per USB-Kabel, per Google Drive Cloud, per Mail an sich selbst mit einer ZIP-Datei des Ordners und anschließendem Herunterladen und Auspacken des Attachments im „Download“-Ordner … oder wie auch immer – jeder Jeck ist anders.

Ich persönlich empfehle hierfür den kostenlosen, werbefreien Total Commander – Dateimanager für Android mitsamt des passenden WiFi/WLAN-Plugin für Totalcmd.

Mit Hilfe dieses Plugins kann man ganze Ordner des Android-Dateisystems im heimischen (W)LAN freigeben und von Finder, Explorer & Co. per WebDAV darauf zugreifen.

Hierzu muss man natürlich die etwas sperrige Freigabe-URL eintippen; alternativ sucht man sich einen QR-Code-Scanner für die Laptop-Webcam (unter macOS etwa das kostenlose „QR Journal“) und ist fein raus.

Anschließend kann man die Dateien einfach per Drag & Drop vom Desktop aufs Handy ziehen. So sieht das Resultat dann (wiederum im Total Commander) am Handy aus:

Text-to-Speech Sprachmodule

Nun zur eigentlichen Vorlesefunktion, auf englisch „Text-to-Speech“ oder kurz „TTS“ genannt. Grundsätzlich beherrschen moderne Android-Handys diese Funktion mit Bordmitteln, entsprechende APIs existieren im Dienste der Barrierefreiheit im Betriebssystem. Maschinelle Vorleser mit verschiedenen Stimmen und unterschiedlich gut gelungener Sprachsynthese, die sich anschließend wahlweise nutzen lassen, gibt es im Google Play-Store herunterzuladen – kostenlos wie kostenpflichtig.

Man findet im Internet verschiedene Vergleichstests darüber, welche Stimme für welchen Zweck besser oder schlechter geeignet ist. Schlussendlich entscheidet aber auch noch der eigene Geschmack. Die mit meinem in Ehre ergrauten Samsung Galaxy S7 mitgelieferte Samsung-Stimme gefällt mir persönlich nicht so sehr, sie klingt arg künstlich.

Aktuell verwende ich stattdessen Googles kostenlos verfügbare Sprachsynthese „Google Sprachausgabe“, die sowohl mit männlicher als auch weiblicher Stimme verschiedenste Sprachen unterstützt, die man sich jeweils in-app dazu laden kann. — Wie gesagt, Geschmäcker sind verschieden.

Vorlesen – there’s an app for that

Das eigentliche Vorlesen von Texten geht natürlich über die reine Handy-Bedienung für Personen mit eingeschränktem Sehvermögen hinaus. Für diesen Zweck muss man mit einer spezialisierten App nachhelfen. Auch derer gibt es mehrere verschiedene im Google Play Store.

Ich persönlich verwende @Voice Aloud Reader, ich habe mir sogar die @Voice Premium Lizenz für aktuell 9,50 EUR gegönnt (mehr dazu weiter unten). @Voice merkt man an, dass er über viele Jahre hinweg entstanden ist und nach und nach immer mehr Features und Einstellmöglichkeiten hinzu gekommen ist. Man kann sich leicht darin verirren, und einiges ist wenig offensichtlich und erfordert anfänglich etwas Herumprobieren.

Man beginnt idealerweise damit, oben links das (schmale) „Burger-Menü“ aufzurufen. Auf der nun erscheinenden, anfangs leeren Seite tippt man unten links auf das „+“, um Dateien hinzuzufügen. Nun kann man sich nun in das gewünschte Verzeichnis durchhangeln, in das man oben die heruntergeladenen .html-Dateien kopiert hatte. — Liegen diese auf der eingelegten SD-Karte, fordert die App typischerweise zur Freigabe von Zugriffsrechten auf.

Dort finden sich alle zum Vorlesen geeigneten Dateien des gewählten Verzeichnisses, und sie lassen sich zum Vorlesen an- oder abwählen – gerne auch alle auf einmal mit dem entsprechenden Symbol oben rechts in der Leiste. Freundlicherweise wird hier „natürlich“ sortiert, d.h. 1…9 kommt vor 10…11…99 kommt vor 100… usw. — Auf „index.html“, das das Inhaltsverzeichnis repräsentiert, kann man getrost verzichten.

Nach „Fertig“ gelangt man zurück auf die zuvor leere Seite, die nun die soeben angewählten Dateien enthält, die man bei Bedarf umsortieren kann. Tippt man nun etwa die oberste an (typischerweise das c’t-Editorial auf „seite-3.html“) und tippt unten rechts auf das „Play“-Symbol, gelangt man zurück zum Hauptbildschirm – und „schon“ geht’s los. Ein Tipp auf den „Pfeil nach oben“ ganz unten rechts klappt das abgebildete Menü aus, auf dem sich die grundlegenden Spracheinstellungen konfigurieren lassen.

  Detailliertere Einstellungen, insbesondere die Wahl der Stimme und entsprechende Feineinstellungen, finden sich im Wust der Programmeinstellungen oben rechts hinter dem Zahnrad-Symbol. Als ungemein wichtig empfinde ich vor allem die erst in der Vollversion freigeschaltete Möglichkeit, Sprachersetzungen zu konfigurieren.

Mitunter wird man nämlich beim Zuhören über Begriffe wie etwa „Liezen-Zart“ stolpern und nach kurzem Nachdenken amüsiert feststellen, dass damit wohl „Lizenz-Art“ gemeint war. Jegliche derartigen Abstrusitäten wird man wohl kaum vorab finden, aber sträflichen Aussprachefehlern wie die meiner Google-Stimme, die dazu neigt, „iOS“ als „Ieh-Oss“ und „macOS“ als „Mah-Koss“ auszusprechen, kann man damit wirksam entgegentreten.

Die merkwürdigen Sonderzeichen vor „iOS“ und „macOS“ rühren übrigens daher, dass diese als „Nur als ganzes Wort“ markiert sind – damit aus „grandios“ nicht etwa also „grand-Ei-Oh-Ess“ ausgesprochen wird.

Wiedergabe und Steuerung per Medientasten am Autoradio

Nachdem man seine persönliche Lieblingsstimme und die optimale Vorlesegeschwindigkeit gefunden hat, gestaltet sich das Vorlesen als überaus angenehm. Richtig nett wird das alles natürlich erst, wenn das Handy per Bluetooth mit dem Autoradio gekoppelt ist und das Playback folglich nicht über den quäkenden Handy-Lautsprecher, sondern über das Auto-Audiosystem erfolgt.

Natürlich wird man zur Navigation im Text nicht das Handy in die Hand nehmen wollen (bzw. auch gar nicht dürfen). Stattdessen unterstützt @Voice zumindest die drei Medientasten Pause, Prev und Next, die das entsprechend ausgestattete Autoradio per Bluetooth ans Handy zurück schickt, und die @Voice entsprechend auswertet.

Dabei gilt: Während des laufenden Playbacks springt ein Druck auf Next/Prev satzweise vor bzw. zurück. Das hilft, wenn man den letzten Satz noch einmal hören möchte, oder wenn man beispielsweise über ein kryptisches Code-Beispiel hinweg skippen möchte, das ungelenk vorgelesen wird.

Der deutlich wichtigere Anwendungsfall ist aber sicher, einen weniger interessanten Artikel abzubrechen und unverzüglich zum nächsten Artikel zu wechseln. Etwas versteckt findet sich in der Anleitung zu @Voice der rettenden Hinweis: Man unterbricht zuerst die Wiedergabe durch Druck auf die Pause-Taste – und drückt erst dann die Next-Taste. Damit springt @Voice tatsächlich in die nächste Datei und damit zum nächsten Artikel.

All das möchte man vielleicht einmal vor Fahrtantritt noch auf dem Parkplatz stehend mit eingeschaltetem Handydisplay ausprobieren, bevor man das Gerät in den Standby schickt und in die Mittelkonsole legt. Man gewöhnt sich aber schnell daran und will es bald nicht mehr missen.

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von GZB – Gero Zahns Blog – ger.oza.hn https://ift.tt/39duF5c

[datasciencepost]

Data Science: The Heart of Big Data

What is data science & why we need it?

Data science deals with the procurement & processing of meaningful data & patterns extracted from a large collection of data belonging to an enterprise, which helps in generating knowledge of business value.

The need for data science arose with the growth of big data & its challenges. In traditional systems, data is structured & easy for enterprises to analyze using BI (Business Intelligence) tools. But as the amount of data collected by an organization grows in size, the data largely remain unstructured & BI tools are not sufficient anymore to process the data. That’s where Data Science comes into the picture. We use more efficient tools of Data Science such as Weka, BigML, R & RapidMiner to process data.

Some common areas where data science is employed are:

Search engines like Google, DuckDuckGo etc. make use of Data science algorithms to search & display results related to our queries.

Speech recognition technologies such as Cortana, Siri, Amazon’s Alexa employ data science in which voices are picked up by a microphone, transcribed into text & respective actions are taken by the machine.

Self-driving cars, drones & autopilot mode in aircrafts.

In social media forums to gather information like detecting the devices you use to access your accounts, whom you interact with & the location from where your account has been accessed.

Spam filters used by e-mail services.

Prediction of diseases in medicine field & gathering information on heart rate, stress levels & blood glucose in humans through wearables such as Fitbit.

What you will be learning in Data Science training

Data acquisition

Predictive analytics

Machine Learning algorithms

Data Mining, Data Structures & data manipulation

Big Data & Hadoop integration with R

Data scientist roles & responsibilities

Prerequisites for learning data science

Data Science has learners from diverse educational backgrounds, and all that is needed to understand the concepts well are, a good command over mathematical & statistical concepts such as algebra, calculus & probability.

Technologies used

Some common data science technologies, tools & languages used are:

Python, R, Java TensorFlow and SQL.

Spark/MLib, Amazon Machine Learning, Hadoop.

Amazon Web Services, Julia, Google Cloud Compute.

Career opportunities in data science

There’s a big demand for data scientists & it is going to further surge in near future. There are 4 kinds of data science roles:

Data Analyst: A data analyst retrieves & gathers data, organizes it and uses it to arrive at important & meaningful conclusions.

Data Engineer: A data engineer is an infrastructure engineer who builds, controls and maintains software infrastructure. A data engineer has good knowledge of distributed systems.

Machine Learning engineer: A machine learning engineer builds, optimizes & deploys machine learning models. These models are treated as components or APIs and plugged into hardwares & apps.

Data science generalist: A generalist does everything starting from retrieval of data, processing it to the final analysis. But it takes many years of experience to get hired as a data science generalist.

Data science is the need of the hour & finds its use in every major field. According to IBM predictions, the demand for Data Scientists will surge to 28% by 2020. Learning data science may not be a walk in the park, but it definitely is thrilling & challenging. So here’s your chance to master the art! Join data science course in Chennai and become expert.

[holytheoristtastemaker]

The Stanford NLP Group recently released Stanza, a new python natural language processing toolkit. Stanza features both a language-agnostic fully neural pipeline for text analysis (supporting 66 human languages), and a python interface to Stanford's CoreNLP java software. Stanza version 1.0.0 is the next version of the library previously known as "stanfordnlp". Researchers and engineers building text analysis pipelines can use Stanza's tools for tasks such as tokenization, multi-word token expansion, lemmatization, part-of-speech and morphological feature tagging, dependency parsing, and named-entity recognition (NER). Compared to existing popular NLP toolkits which aid in similar tasks, Stanza aims to support more human languages, increase accuracy in text analysis tasks, and remove the need for any preprocessing by providing a unified framework for processing raw human language text. The table below comparing features with other NLP toolkits can be found in Stanza's associated research paper. Stanza's pipeline is trained on 112 datasets, including many multilingual corpora like the Universal Dependencies (UD) treebanks. The UD project attempts to facilitate multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective by developing cross-linguistically consistent treebank annotation for over 70 languages. The fully neural architecture applied to Stanza generalizes well as it helps achieve competitive performance on all languages tested. The research paper displays the results after tests run on the UD treebanks dataset and a multilingual NER dataset. On the UD treebanks, Stanza shows that it's language-agnostic pipeline architecture is able to adapt to different languages by scoring the highest macro-averaged scores over 100 treebanks which covers 66 languages. On the NER component, Stanza achieves similar F1 scores to FLAIR (on 75% smaller NER models) and outperforms spaCy. Stanza also offers a python interface for accessing Stanford's Java CoreNLP software which provides additional tools to NLP practitioners. Taking advantage of CoreNLP's existing server interface, Stanza adds a robust client which starts up the CoreNLP server automatically as a local process when the client is instantiated. The client communicates with the server through RESTful APIs. In the future the team behind Stanza hopes to provide an interface for outside researchers to contribute their models, improve the computational efficiency, and extend the functionalities by implementing other processors. The team at spaCy quickly migrated spacy-stanza (which allows users to import Stanza models as spaCy pipelines) to work with this new API.

http://damianfallon.blogspot.com/2020/03/stanford-nlp-group-releases-stanza.html

[coolcipher91stuff-blog]

The Best Email and SMS Marketing Company

The best email and SMS Company has marketing a priority for your business in 2020? Are you looking for the best email and SMS marketing software?

Choosing the right email and SMS marketing service can have a significant impact on the success of your marketing campaign.

Why Choosing the Best Email & SMS Marketing Service is Important?

Email and SMS marketing is one of the most cost-effective marketing tools for small businesses. According to the Direct Marketing Association, email & SMS marketing on average sees a 4500 percent return on investment for businesses in India. This is because email and SMS marketing is easy to manage, gives you full control, and allows you to establish a direct contact with your customers.

 Ø Cheapest Bulk SMS Provider in India

The method of Bulk Email service provider and Bulk SMS service provider has reliably been to give standard stages to allow any client to quickly pass on any SMS administration. Our bulk email sending services game plans are away to deliver enduring prompts our clients from arranged establishment. We set up together a movement of elevating philosophies to achieve best outcomes for our respect customers.

The Voice SMS Services provider brings business and hence is being used as an effective marketing tool these days. If the message is conveyed in local language, it attracts more visitors. And voice telephony services are therefore the right choice for your all business needs. Our Voice SMS Services provider is designed to make communication personalized and effective.

Outbound dialer solutions provide you the numbers to which you can call and get your messages recorded in your own voice. You can also upload a clip or text which will be automatically converted to speech. These messages can be immediately transferred to the groups or individuals in the form of automated phone calls .The outbound dialer software is the best to deploy for asking feedback or opinion from the users while using our web interface.

Promotional SMS service provider is those SMS which are planned to advance organization/item/administrations to individuals, chiefly utilized for advertising purpose. The Promotional bulk SMS service is as a rule proposed to pass on fundamental data to each one of the individuals who are a piece of the exchange or known individuals/gathering. Promotional SMS service provider Send offers or promotional news to your existing or new customers. Send promotional bulk SMS service between 9AM to 9PM without any interruption to non-DND numbers.

 How to apply for transactional SMS route?

Transactional SMS service provider is used for sending necessary information to the customers regarding a product or service. Examples are e-commerce sites, sending messages of order invoice number, delivery status, receipt of transaction etc to its customers. Transactional SMS reseller basically the transactional route is used by companies and organizations who want to send non promotional SMS to both DND and non DND numbers 24*7. You can send the message without approval.

Ø Features of Transactional SMS

1. In the transactional route you are eligible to send SMS without approval.

2. In this route messages can be sent to both DND and non DND numbers.

3. You can send SMS 24*7, without any time restraints.

4. The SMS gets delivered instantly without any hassle.

5. SMS can be sent using your own Sender ID.

 International bulk SMS service provider is a leading Bulk SMS services provider across the globe. Our bulk SMS will help you increase your sales and maintain better customer satisfaction.

Using our Bulk SMS services is very simple and easy. Contact us today and start sending your SMS to your clients in no time.

Bulk SMS Worldwide, Targeted SMS to Worldwide and Free SMS to Worldwide,

Send Bulk SMS to Worldwide using our SMS services and get the real feedback you deserve.

International SMS service is an innovative end-to-end SMS provider of interactive digital marketing services, email marketing, and mobile SMS marketing campaigns.

International SMS service to Worldwide enables companies to communicate real-time with their customers anytime, anywhere by pushing information directly to the customer's mobile phones...

Ø Why International SMS Service?

·         Large SMS International Coverage

·         Fast SMS Delivery

·         24/7 SMS Support

·         No Setup Charge for any SMS account

·         No Minim SMS to Purchase

·         No Hidden Cost for any SMS package

·         No Port Fees for SMS

 The Bulk SMS API services with your website via Logon utility SMS API. Bulk SMS API is best way to send automated Bulk SMS directly from your platform. We are here to serve you with our ultra-fast and highly reliable

promotional

email services

. We are the Best

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Email Marketing

Company are an award-winning and trusted conglomerate, which strives for perfection in delivering all results performance to our clients irrespective of their size. Our product range encompasses all tools of electronic marketing like Best Full Service in Bulk Email, Mass Email, Email Marketing, Mail Server, SMTP Provider, Email Server Hosting, Bulk SMTP Server, Dedicated SMTP Server, and you name it, we have one. We have an array of conceptualized programs with latest tracking software that matches the requirements of all customers with maximum compatibility.

 Your database of contacts is highly valuable, and you can leverage it to stay connected with your customers, nurture your leads and eventually grow your online audience. Email newsletter service are your best bet if you need to nurture leads, sell to your existing customers, and drive targeted traffic to your website. However, newsletter writing service headline that results in swelled open and click-through rates can be a bit of science and that’s why you need our awesome experienced copywriting team!

With our Email Acquisition Companies for email writing service, you can disseminate fresh and relevant content that will help you stay on top of the mind of your customers. Being there in the customers’ inbox will enhance your company’s image, and help position your business as an established thought leader in the industry.

Email acquisition campaigns & experienced writers can create emails and newsletters that give you a distinct competitive advantage, and effectively engage prospects in a way that you will have a constant pipeline of potential sales.

 Ø Let’s look at some retention techniques applied to retention email marketing.

1. Create and send useful content 2. Invite customers to webinars and courses 3. Send recap emails about the customer’s activity 4. Design a product newsletter 5. Take advantage of the potential of milestone emails 6. Engage inactive customers 7. Support retention: on boarding, new launches, cross-selling, and up selling

 Our advice is to develop a retention email marketing strategy, defining a set of campaigns and then checking their effectiveness. You can start today with email retention software by requesting a free MailUp trial: you’ll have the platform available for 30 days to create, send, and track your campaigns.

Outbound dialer solutions have been around for many years, and even today there are certain types of calling campaigns that use them effectively. Fundamentally, predictive dialer algorithms that calculate when the next agent will be available and places calls based on those calculations to maintain agent activities at the maximum extent. Outbound dialer software that maintains to a drop call % setting of 3% or less, which the domestic regulated percent is of dropped or undropped calls. The key to a great outbound system is really the ability to control and segment your lists and campaign settings to allow you to target individuals for certain calling times.  Although outbound predictive dialers have been around for a long time, they are not all created equal.

Missed Call service is one of the most effective methods of lead generation as it involves minimal efforts and virtually no costs on the part of the customer. Be it for generating leads or collecting customer feedback, integrating missed call services with marketing campaigns offers time-tested efficiency. Missed call solution also enables businesses to conduct polls and surveys for market research, leading to better ROI, and higher customer satisfaction. Moreover, it makes handling start-stop of services a breeze, both for the customers and the company. Web-based missed call services generate analytics data, record alerts, and works with other IVR services to send automated acknowledgment SMS to the callers.

Ø FEATURES OF MISSED CALL SERVICES

1.     Automated hassle-free mode 2.     Unlimited call reporting 3.     Zero cost to callers 4.     Fast and effective 5.     Works with landline 6.     API support

Ø ADVANTAGES OF MISSED CALL SERVICE

Easy to integrate with your own app or     website with complete API support from our team

Easy to assimilate with a range of toll     free and virtual mobile numbers from our services for an extensive     campaign

Automated call disconnection for easy use     of missed call service

Prompt acknowledgement SMS delivery

Detailed reports on missed calls received     to analyze call time, response time and duration, throughput performances     etc.

 Ø What is an IVR Solution?

An Interactive Voice Response System is your business automated attendant. When you place a call to a business, there is a voice that greets you politely with a welcome message and then helps you navigate to the solution - all without the help of a real agent. This is how interactive voice response service helps you enhance customer service and create a better experience for your leads with zero waiting time. Save costs by reducing churn and retaining your customers!

Customer care toll free numbers make businesses sound more professional. You can make a call to a toll free number, to reach businesses and/or individuals, without being charged for the call. Since the customer support is free, it creates goodwill and a loyal customer base. Here, Customer care executive number provides you with a useful tool called Toll Free Number Finder. It helps the people in India contact the customer care help desk of any company they need to get in touch with. This service provides you the complete list of toll free numbers in India of all businesses, along with their company website address.

Call center services can include any business that can be done by phone from telephone answering service to handling customer service calls, call answering service and supporting product recalls. Outsourcing these activities saves on staffing, office space, equipment and other overhead costs and frees you up to focus on your core business.

Ø The Benefits of call center services

1.     Always be available

2.     Reduce overheads

3.     Never miss a lead

4.     Protect your data

5.     Trust us to handle it

6.     24/7 order handling

7.     Stay updated

Ø The Benefits of call answering service

1.     Extend your opening hours

2.     2. Achieve 100% productivity

3.     3. Better for business

 Audio Conferencing Solution provides call Quality, Number of Participants allowed, Mobility, Ease-of-use,  Member visibility, Internet-dependency and Flexibility are the main capabilities that any call conferencing solution should have to qualify as a good conference call provider. Audio conferencing service providers are some other aspects like access to call recordings, and auto-scheduling capabilities that are important as well.

[tastydregs]

ChatGPT's API Is Here. Let the AI Gold Rush Begin

When OpenAI, the San Francisco company developing artificial intelligence tools, announced the release of ChatGPT in November 2022, former Facebook and Oculus employee Daniel Habib moved quickly.

Within four days of ChatGPT’s launch, Habib used the chatbot to build QuickVid AI, which automates much of the creative process involved in generating ideas for YouTube videos. Creators input details about the topic of their video and what kind of category they’d like it to sit in, then QuickVid interrogates ChatGPT to create a script. Other generative AI tools then voice the script and create visuals.

Tens of thousands of users used it daily—but Habib had been using unofficial access points to ChatGPT, which limited how much he could promote the service and meant he couldn’t officially charge for it. That changed on March 1, when OpenAI announced the release of API access to ChatGPT and Whisper, a speech recognition AI the company has developed. Within an hour, Habib hooked up QuickVid to the official ChatGPT API.

“All of these unofficial tools that were just toys, essentially, that would live in your own personal sandbox and were cool can now actually go out to tons of users,” he says. 

OpenAI’s announcement could be the start of a new AI goldrush. What was previously a cottage industry of hobbyists operating in a licensing gray area can now turn their tinkering into fully-fledged businesses.

“What this release means for companies is that adding AI capabilities to applications is much more accessible and affordable,” says Hassan El Mghari, who runs TwitterBio, which uses ChatGPT’s computational power to generate Twitter profile text for users.

OpenAI has also changed its data retention policy, which could reassure businesses thinking of experimenting with ChatGPT. The company has said it will now only hold on to users’ data for 30 days, and has promised that it won’t use data that users input to train its models. 

That, according to David Foster, partner at Applied Data Science Partners, a data science and AI consultancy based in London, will be “critical” for getting companies to use the API.

Foster thinks the fear that personal information of clients or business critical data could be swallowed up by ChatGPT’s training models was preventing them from adopting the tool to date. “It shows a lot of commitment from OpenAI to basically state, ‘Look, you can use this now, risk-free for your company. You’re not going to find your company’s data turning up in that general model,’” he says.

This policy change means that companies can feel in control of their data, rather than have to trust a third party—OpenAI—to manage where it goes and how it’s used, according to Foster. “You were building this stuff effectively on somebody else’s architecture, according to somebody else’s data usage policy,” he says. 

This, combined with the falling price of access to large language models, means that there will likely be a proliferation of AI chatbots in the near future.

API access to ChatGPT (or more officially, what OpenAI is calling GPT3.5) is 10 times cheaper than access to OpenAI’s lower-powered GPT3 API, which it launched in June 2020, and which could generate convincing language when prompted but did not have the same conversational strength as ChatGPT.

“It’s much cheaper and much faster,” says Alex Volkov, founder of the Targum language translator for videos, which was built unofficially off the back of ChatGPT at a December 2022 hackathon. “That doesn’t happen usually. With the API world, usually prices go up.” 

That could change the economics of AI for many businesses, and could spark a new rush of innovation. 

“It’s an amazing time to be a founder,” QuickVid’s Habib says. “Because of how cheap it is and how easy it is to integrate, every app out there is going to have some type of chat interface or LLM [large language model] integration … People are going to have to get very used to talking to AI.”

[ict-marketresearch-reports]

Speech to text API Market Innovations, Technology Growth and Research -2026

According to a research report "Speech to text API Market Forecast by Component (Software and Services), Application (Fraud Detection & Prevention, Content Transcription, Subtitle Generation), Deployment Mode, Organization Size, Vertical, and Region - Global Forecast to 2026" published by MarketsandMarkets, the market for Speech-to-text API is projected to grow from USD 2.2 billion in 2021 to USD 5.4 billion by 2026; it is expected to grow at a CAGR of 19.2% during 2021–2026.

The COVID-19 pandemic has impacted trading activities across regions. It has had a moderate impact on all elements of the technology sector. The hardware business is predicted to be the most impacted in the IT industry. Owing to the slowdown of hardware supply and reduced manufacturing capacity, the IT infrastructure growth has slowed down. Businesses providing solutions and services are also expected to slow down for a short period. However, the adoption of collaborative applications, analytics, security solutions, and AI is set to increase in the remaining part of the year. Verticals such as manufacturing, retail, and energy and utilities have witnessed a moderate slowdown, whereas BFSI, government, and healthcare and life sciences verticals have witnessed a minimal impact. Moreover, with recovery, global ICT spending is estimated to increase by approx. 3.5%-4.5% from 2020 to 2021. The impact of COVID-19 is believed to be short-term; however, it may have a significant effect on businesses and forecasts to a significant extent for a minimum of 8-12 months.

During the pandemic, many companies experienced a significant increase in pressure from customers, while their number of available employees decreased. Many contact centers were unable to cope with demand or closed because of lockdown restrictions, leading to long delays in customer service queries, which significantly affected the customer experience. As businesses develop a more strategic approach that delivers resilience into operations through the flexibility and scalability while at the same time working to improve operational efficiencies, so speech-to-text API is rising to the forefront of technology enablers.

Data analytics application builders are seeking medical speech recognition capabilities that help them efficiently and accurately transcribe video and audio containing COVID-19 terminology into text for downstream analytics. For instance, AWS offers Amazon Transcribe Medical, which is a fully managed speech recognition (ASR) service that makes it easy to add medical speech-to-text capabilities to any application. Powered by deep learning, the service offers a ready-to-use medical speech recognition model that users can integrate into a variety of voice applications in the healthcare and life sciences domain. Users can use the custom vocabulary feature to accurately transcribe more specific medical terminologies, such as medicine names, product brands, medical procedures, illnesses, or COVID-19-related terminology.

The services segment to hold higher CAGR during the forecast period

Based on components, the market size of the software segment is expected to hold a larger market share in 2021, while the services segment is projected to grow at a higher CAGR during the forecast period. This can be attributed to the need for determining the time and cost required to install the API/software tools that require fully managed speech-to-text API services. The high growth is attributed to the higher adoption of speech-to-text API solutions across key verticals, such as BFSI, media and entertainment, and retail and eCommerce.

The cloud segment to hold the larger market size during the forecast period

Based on deployment mode the speech-to-text API market is bifurcated into on-premises and cloud. The market size and CAGR of the cloud segment are estimated to be higher than the on-premises segment during the forecast period. The cloud technology benefits of easy deployment and minimal capital requirement facilitate the adoption of the cloud deployment model. The adoption of cloud-based speech-to-text API solutions is expected to be supported by the COVID-19 pandemic, as lockdowns and social distancing practices are encouraging companies to move to cloud solutions that can be managed remotely. The increasing demand for scalable, easy-to-use, and cost-effective speech-to-text API solutions is expected to accelerate the growth of the cloud segment in the speech-to-text API market.

The large enterprises segment to hold a larger market size during the forecast period

The large enterprises segment is estimated to hold a larger market share in 2021. The growth of the segment is due to increased competition in large enterprises from budding SMEs. Owing to the availability of cost-effective cloud solutions, speech-to-text API solutions and services are expected to witness a prominent growth rate among SMEs during the forecast period.

Healthcare and life sciences vertical is to have the highest CAGR during the forecast period

The healthcare and life sciences segment is projected to grow at the highest CAGR during the forecast period. Speech-to-text API helps financial institutions effortlessly connect with customers to provide an enhanced customer experience. The need for rapid diagnosis, healthcare data analysis, and better patient care is expected to drive the growth of the healthcare and life sciences vertical in the APAC region.

North America to hold the largest market share during the forecast period

In North America is expected to hold the largest market size in 2021. In North America, speech-to-text API/software tools and services are highly effective in most organizations due to the increasing need to extract meaningful insights from voice data to enhance user experience. APAC is expected to hold the largest CAGR during the forecast period, while Latin America and MEA are slowly picking up speech-to-text API due to its benefits for various industries to get user insights.

Key players offering Speech-to-text API market. The major vendors covered Google (US), Microsoft (US), AWS (US), IBM (US), Verint (US), Baidu (China), Twilio (US), Speechmatics (UK), VoiceCloud (US), VoiceBase (US), Voci (US), Kasisto (US), Nexmo (US), Contus (India), GoVivace (US), GL Communications (US), Wit.ai (US), VoxSciences (US), Rev (US), Vocapia Research (France), Deepgram (US), Otter.ai (US), AssemblyAI (US), Verbit (US), Behavioral Signals (US), Chorus.ai (US), Gnani.ai (India), Sayint.ai (India), and Amberscript (Netherlands).

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Speech-to-text API Market 2022 Global Industry Share, Growth, Drivers, Emerging Technologies, and Forecast Research Report 2028

Speech-to-text API Market 2022-2030

A New Market Study, Titled “Speech-to-text API Market Upcoming Trends, Growth Drivers and Challenges” has been featured on fusionmarketresearch.

Description

This global study of the Speech-to-text API Market offers an overview of the existing market trends, drivers, restrictions, and metrics and also offers a viewpoint for important segments. The report also tracks product and services demand growth forecasts for the market. There is also to the study approach a detailed segmental review. A regional study of the global Speech-to-text API industry is also carried out in North America, Latin America, Asia-Pacific, Europe, and the Near East & Africa. The report mentions growth parameters in the regional markets along with major players dominating the regional growth.

Request Free Sample Report @ https://www.fusionmarketresearch.com/sample_request/Speech-to-text-API-Market/39749

The report offers detailed coverage of Speech-to-text API industry and main market trends with impact of coronavirus. The market research includes historical and forecast market data, demand, application details, price trends, and company shares of the leading Speech-to-text API by geography. The report splits the market size, by volume and value, on the basis of application type and geography.

The major players included in the report are Google (US) Microsoft (US) IBM (US) AWS (US) Nuance Communications (US) Verint (US) Speechmatics (England) Vocapia Research (France) Twilio (US) Baidu (China) Facebook (US) iFLYTEK (China) Govivace (US) Deepgram (US) Nexmo (US) VoiceBase (US) Otter.ai (US) Voci (US) GL Communications (US) Contus (India)

Based on the type of product, the global Speech-to-text API market segmented into On-premises Cloud

Based on the end-use, the global Speech-to-text API market classified into Financial Services and Insurance Telecommunications and Information Technology Health Care Retail and E-commerce Government and Defense Others

Based on geography, the global Speech-to-text API market segmented into North America (United States, Canada and Mexico) Europe (Germany, UK, France, Italy, Russia and Spain etc.) Asia-Pacific (China, Japan, Korea, India, Australia and Southeast Asia etc.) South America (Brazil, Argentina and Colombia etc.) Middle East & Africa (South Africa, UAE and Saudi Arabia etc.)

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Table of Contents

1 RESEARCH SCOPE 1.1 Research Product Definition 1.2 Research Segmentation 1.2.1 Product Type 1.2.2 Main product Type of Major Players 1.3 Demand Overview 1.4 Research Methodology

2 GLOBAL Speech-to-text API INDUSTRY 2.1 Summary about Speech-to-text API Industry

2.2 Speech-to-text API Market Trends 2.2.1 Speech-to-text API Production & Consumption Trends 2.2.2 Speech-to-text API Demand Structure Trends 2.3 Speech-to-text API Cost & Price

3 MARKET DYNAMICS 3.1 Manufacturing & Purchasing Behavior in 2020 3.2 Market Development under the Impact of COVID-19 3.2.1 Drivers 3.2.2 Restraints 3.2.3 Opportunity 3.2.4 Risk

4 GLOBAL MARKET SEGMENTATION 4.1 Region Segmentation (2017 to 2021f) 4.1.1 North America (U.S., Canada and Mexico) 4.1.2 Europe (Germany, UK, France, Italy, Rest of Europe) 4.1.3 Asia-Pacific (China, India, Japan, South Korea, Southeast Asia, Australia, Rest of Asia Pacific) 4.1.4 South America (Brazil,, Argentina, Rest of Latin America) 4.1.5 Middle East and Africa (GCC, North Africa, South Africa, Rest of Middle East and Africa) 4.2 Product Type Segmentation (2017 to 2021f) 4.2.1 On-premises 4.2.2 Cloud 4.3 Consumption Segmentation (2017 to 2021f) 4.3.1 Financial Services and Insurance 4.3.2 Telecommunications and Information Technology 4.3.3 Health Care 4.3.4 Retail and E-commerce 4.3.5 Government and Defense 4.3.6 Others

5 NORTH AMERICA MARKET SEGMENT 5.1 Region Segmentation (2017 to 2021f) 5.1.1 U.S. 5.1.2 Canada 5.1.3 Mexico 5.2 Product Type Segmentation (2017 to 2021f) 5.2.1 On-premises 5.2.2 Cloud 5.3 Consumption Segmentation (2017 to 2021f) 5.3.1 Financial Services and Insurance 5.3.2 Telecommunications and Information Technology 5.3.3 Health Care 5.3.4 Retail and E-commerce 5.3.5 Government and Defense 5.3.6 Others 5.4 Impact of COVID-19 in North America

What our report offers: – Market share assessments for the regional and country-level segments – Strategic recommendations for the new entrants – Covers Market data for the years 2020, 2021, 2022, 2025, and 2028 – Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations) – Strategic recommendations in key business segments based on the market estimations – Competitive landscaping mapping the key common trends – Company profiling with detailed strategies, financials, and recent developments – Supply chain trends mapping the latest technological advancements

Free Customization Offerings: All the customers of this report will be entitled to receive one of the following free customization options: • Company Profiling o Comprehensive profiling of additional market players (up to 3) o SWOT Analysis of key players (up to 3) • Regional Segmentation o Market estimations, Forecasts and CAGR of any prominent country as per the client’s interest (Note: Depends on feasibility check) • Competitive Benchmarking o Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances