#ibm watson tts

[cybersecurityict]

AI Voice Generators Market Size, Share, Analysis, Forecast, and Growth Trends to 2032: Technological Advancements Driving Expansion

The AI Voice Generators Market was valued at USD 3.20 billion in 2023 and is expected to reach USD 40.25 billion by 2032, growing at a CAGR of 32.51% from 2024-2032.

The AI Voice Generators Market is undergoing rapid transformation driven by advancements in machine learning, neural networks, and speech synthesis technologies. These systems are increasingly adopted across sectors like entertainment, e-learning, customer service, and healthcare to enhance user engagement and streamline communication. With the rise in demand for personalized and natural-sounding voiceovers, AI voice generators are becoming an essential tool for content creators, enterprises, and developers alike. Their ability to deliver human-like intonation, emotion, and contextual understanding is reshaping the digital voice landscape.

AI Voice Generators Market is also witnessing a surge in innovation through multilingual capabilities and real-time voice synthesis, opening new opportunities for global scalability. These tools are revolutionizing how brands interact with their customers by offering hyper-personalized experiences in dynamic environments. The integration of AI voices in smart devices, virtual assistants, and accessibility technologies further strengthens the market's foothold as voice interfaces become integral to digital ecosystems.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/5985 

Market Keyplayers:

Amazon Web Services, Inc. (Amazon Polly, AWS Lex)

Cisco Systems, Inc. (Cisco Webex, Cisco Kinetic)

ElevenLabs (Eleven Voice, Eleven Text-to-Speech)

Google LLC (Google Cloud Text-to-Speech, Google Assistant)

International Business Machines Corporation (IBM Watson Text to Speech, IBM Cloud)

Inworld AI (Inworld AI Voice, Inworld AI Integration)

Microsoft (Azure Speech, Microsoft Cognitive Services)

OpenAI (ChatGPT, OpenAI Codex)

Resemble AI (Resemble Voice, Resemble API)

SoundHound AI Inc. (SoundHound, Houndify)

NVIDIA (NVIDIA Riva, NVIDIA Jarvis)

Meta (Meta AI, Facebook AI)

Voicemod (Voicemod Voice Changer, Voicemod Studio)

Descript (Overdub, Descript Studio)

Simplified (Text-to-Speech, AI Writer)

Soundful (Soundful Music Generator, Soundful Voice AI)

DeepBrain AI (DeepBrain AI Speech Synthesis, DeepBrain AI Voice Cloning)

Baidu, Inc. (Baidu Deep Voice, Baidu Apollo)

Samsung Group (Samsung Bixby, Samsung Speech SDK)

Synthesia (Synthesia Studio, Synthesia AI Video)

Speechelo (Speechelo TTS, Speechelo Pro)

Cerence Inc. (Cerence Voice, Cerence AI Assistant)

WellSaid Labs (WellSaid TTS, WellSaid Studio)

CereProc Ltd. (CereVoice, CerePro)

Listnr AI (Listnr AI Voice, Listnr AI API)

Respeecher (Respeecher Voice Cloning, Respeecher Speech Synthesis)

Speechki (Speechki Voice, Speechki TTS)

Market Analysis

The market is characterized by a growing ecosystem of startups and tech giants investing in cutting-edge voice AI models. The increasing need for efficient audio production, combined with cost and time savings, is pushing businesses to adopt these solutions at scale. North America leads in adoption due to technological readiness, while Asia-Pacific is emerging as a fast-growing hub driven by digital transformation in regional languages.

Market Trends

Surge in demand for text-to-speech (TTS) solutions in content localization and dubbing

Rising use of AI-generated voices in audiobooks, podcasts, and video narration

Integration of voice cloning and synthetic speech in customer support automation

Advancements in emotion-driven voice generation for immersive experiences

Increased emphasis on ethical voice synthesis and identity protection

Expansion of real-time voice translation for cross-border communication

Growing partnerships between AI voice startups and media production companies

Market Scope

The AI Voice Generators Market spans a wide array of applications across sectors such as media & entertainment, telecommunications, e-learning, healthcare, retail, and automotive. These solutions are being integrated into mobile apps, smart devices, virtual assistants, and accessibility tools to improve user interaction and inclusivity. From enabling voice accessibility in education for differently-abled users to enriching gaming experiences with real-time narration, the market is evolving to support diverse and scalable use cases.

Market Forecast

The market is expected to continue on a strong growth trajectory as demand for high-quality, scalable voice synthesis solutions accelerates. Emerging innovations in generative AI models and neural TTS systems are anticipated to reduce latency, improve naturalness, and support more nuanced speech outputs. The future landscape will see more real-time, multilingual, and emotionally intelligent voices embedded into business ecosystems, driving more engaging, inclusive, and automated interactions.

Access Complete Report: https://www.snsinsider.com/reports/ai-voice-generators-market-5985 

Conclusion

As digital content and conversational interfaces dominate the future of communication, the AI Voice Generators Market stands at the forefront of this revolution. Its evolution is not just about speaking with machines—it's about making machines speak like us. In a world craving faster, smarter, and more relatable voice-driven experiences, AI voice technology is setting the stage for a more connected and human-centric future.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[christianbale121]

AI Agent Development: A Comprehensive Guide to Building Intelligent Virtual Assistants

Artificial Intelligence (AI) is reshaping industries, and AI agents are at the forefront of this transformation. From chatbots to sophisticated virtual assistants, AI agents are revolutionizing customer service, automating tasks, and enhancing user experiences. In this guide, we will explore AI agent development, key components, tools, and best practices for building intelligent virtual assistants.

What is an AI Agent?

An AI agent is an autonomous software entity that perceives its environment, processes information, and takes actions to achieve specific goals. AI agents are commonly used in virtual assistants, customer service bots, recommendation systems, and even robotics.

Types of AI Agents

AI agents can be classified based on their capabilities and autonomy levels:

Reactive Agents – Respond to inputs but do not retain memory or learn from past interactions.

Limited Memory Agents – Store past interactions for better decision-making (e.g., chatbots with short-term memory).

Theory of Mind Agents – Understand user emotions and beliefs, improving personalized responses (still in development).

Self-Aware Agents – Theoretical AI that possesses self-awareness and reasoning (future concept).

Key Components of AI Agent Development

To build a functional AI agent, you need several core components:

1. Natural Language Processing (NLP)

NLP enables AI agents to understand, interpret, and generate human language. Popular NLP frameworks include:

OpenAI GPT models (e.g., ChatGPT)

Google Dialogflow

IBM Watson Assistant

2. Machine Learning & Deep Learning

AI agents rely on ML and deep learning models to process data, recognize patterns, and improve over time. Some common frameworks include:

TensorFlow

PyTorch

Scikit-learn

3. Speech Recognition & Synthesis

For voice assistants like Siri and Alexa, speech-to-text (STT) and text-to-speech (TTS) capabilities are essential. Tools include:

Google Speech-to-Text

Amazon Polly

Microsoft Azure Speech

4. Conversational AI & Dialogue Management

AI agents use dialogue management systems to maintain coherent and context-aware conversations. Technologies include:

Rasa (open-source conversational AI)

Microsoft Bot Framework

Amazon Lex

5. Knowledge Base & Memory

AI agents can store and retrieve information to enhance responses. Common databases include:

Vector databases (e.g., Pinecone, FAISS)

Knowledge graphs (e.g., Neo4j)

6. Integration with APIs & External Systems

To enhance functionality, AI agents integrate with APIs, CRMs, and databases. Popular API platforms include:

OpenAI API

Twilio for communication

Stripe for payments

Steps to Build an AI Virtual Assistant

Step 1: Define Use Case & Goals

Decide on the AI agent’s purpose—customer support, sales automation, or task automation.

Step 2: Choose a Development Framework

Select tools based on requirements (e.g., GPT for chatbots, Rasa for on-premise solutions).

Step 3: Train NLP Models

Fine-tune language models using domain-specific data.

Step 4: Implement Dialogue Management

Use frameworks like Rasa or Dialogflow to create conversation flows.

Step 5: Integrate APIs & Databases

Connect the AI agent to external platforms for enhanced functionality.

Step 6: Test & Deploy

Perform extensive testing before deploying the AI agent in a real-world environment.

Best Practices for AI Agent Development

Focus on User Experience – Ensure the AI agent is intuitive and user-friendly.

Optimize for Accuracy – Train models on high-quality data for better responses.

Ensure Data Privacy & Security – Protect user data with encryption and compliance standards.

Enable Continuous Learning – Improve the AI agent’s performance over time with feedback loops.

Conclusion

AI agent development is revolutionizing business automation, customer engagement, and personal assistance. By leveraging NLP, ML, and conversational AI, developers can build intelligent virtual assistants that enhance efficiency and user experience. Whether you’re developing a simple chatbot or a sophisticated AI-powered agent, the right frameworks, tools, and best practices will ensure success.

[zarazyana]

How Can You Build an Effective AI Agent for Customer Support?

In today’s digital age, customer support has transformed from a reactive to a proactive function, evolving into a pivotal part of the customer experience. Traditional support methods are being replaced by AI agents—intelligent systems designed to interact with users, resolve queries, and deliver 24/7 assistance. Developing an effective AI agent development for customer support can enhance user satisfaction, streamline operations, and reduce costs. But how do you create an AI agent that’s both capable and customer-friendly?

This guide will walk you through the essential steps, technologies, and best practices to develop an AI-driven customer support agent that aligns with modern business needs.

1. Understanding the Role of AI Agents in Customer Support

AI agents for customer support are software programs powered by Artificial Intelligence, specifically designed to understand customer queries, retrieve information, and resolve issues autonomously. These agents can range from basic chatbots that follow pre-set rules to sophisticated virtual assistants equipped with Natural Language Processing (NLP) and Machine Learning (ML) capabilities that learn and improve over time.

Key benefits of AI customer support agents include:

24/7 Availability: AI agents can work around the clock, catering to users in different time zones.

Scalability: They can handle multiple queries simultaneously, reducing wait times.

Cost Efficiency: AI agents lower operational costs by minimizing human intervention for routine queries.

Enhanced Customer Satisfaction: Quick, accurate responses improve customer experience.

2. Defining Objectives and Scope for Your AI Agent

Before diving into development, define your agent’s role within your customer support strategy. Understanding your objectives and setting clear expectations will help guide the development process.

Consider these questions:

What are the primary functions of the AI agent? (e.g., answering FAQs, troubleshooting, processing returns)

What type of user interactions will it handle? (text, voice, or a combination)

What level of complexity is required? A rule-based agent may suffice for simple inquiries, whereas a learning-based agent might be needed for nuanced interactions.

How will the AI agent integrate with existing support channels? Ensure it aligns with your CRM and support ticket systems.

Having clear goals will help shape the architecture, technology stack, and training data you’ll need.

3. Choosing the Right Technology Stack

Building an effective AI agent requires a mix of core technologies that enable understanding, processing, and responding to customer inputs:

a. Natural Language Processing (NLP)

NLP allows AI agents to understand and interpret human language, the backbone of conversational AI. With NLP, the agent can analyze user intent, sentiment, and even nuances in language.

Popular NLP tools and libraries:

OpenAI’s GPT (Generative Pre-trained Transformer)

Google’s Dialogflow

IBM Watson Assistant

Microsoft Azure Bot Service

SpaCy and NLTK (Natural Language Toolkit) for more customized solutions

b. Machine Learning (ML) and Deep Learning (DL)

ML and DL algorithms allow your AI agent to improve over time. Through training, the agent learns patterns in customer interactions, enabling it to handle increasingly complex queries and provide better responses.

Key ML tools:

TensorFlow and Keras: Ideal for training custom ML models.

PyTorch: Popular for complex neural networks and NLP applications.

Scikit-Learn: Great for basic machine learning models and data processing.

c. Automated Speech Recognition (ASR) and Text-to-Speech (TTS)

For voice-based agents, ASR converts spoken language into text, while TTS transforms responses into natural-sounding speech.

Popular ASR and TTS tools:

Google’s Text-to-Speech API

Amazon Polly

Microsoft Azure Speech API

d. Integration with CRM and Backend Systems

An effective AI agent for customer support should integrate seamlessly with existing systems, such as:

Customer Relationship Management (CRM) platforms (e.g., Salesforce, HubSpot) for storing customer data and support tickets.

Ticketing Systems (e.g., Zendesk, Freshdesk) to automate the process of logging, escalating, and resolving support issues.

Knowledge Bases: Having access to product information and FAQs helps the AI agent deliver accurate responses.

4. Designing the User Experience (UX) for Your AI Agent

An AI agent’s success is significantly influenced by its usability and the overall user experience it offers. A well-designed interface and response structure are crucial for customer engagement.

UX Best Practices:

Conversational Flow: Plan out common user journeys, scripting responses for various types of inquiries and guiding users toward solutions.

Personalized Interactions: Use customer data to personalize responses, greeting users by name, or remembering past interactions to provide relevant answers.

Clear Escalation Options: If the AI agent cannot resolve an issue, it should smoothly transfer the query to a human agent. Clear messages about escalation build trust.

Natural Tone and Language: Avoid robotic phrasing. The more conversational the tone, the more users will feel comfortable interacting with the agent.

5. Data Collection and Training the AI Agent

The effectiveness of your AI agent relies on its training data. Training an agent involves providing it with enough examples of customer queries, responses, and possible variations.

Data Sources for Training:

Historical Chat Transcripts: Gather past conversations between customers and support agents to create realistic training data.

FAQs and Knowledge Base Articles: Ensure the agent is trained on the most common customer inquiries.

User Feedback and Surveys: Use feedback to improve the agent’s responses, focusing on areas where it may be lacking or misunderstood queries.

Key Considerations in Training:

Supervised Learning: For high-quality responses, use labeled data where customer queries are matched with correct responses.

Continuous Learning: Establish mechanisms for ongoing learning so the AI agent can adapt based on recent interactions and emerging customer trends.

Handling Variations in Language: Train the AI agent to recognize different ways customers may phrase questions, including slang, typos, and colloquial language.

6. Testing the AI Agent

Once trained, rigorous testing is crucial before deploying your AI agent to ensure accuracy and a seamless user experience.

Types of Testing:

Functionality Testing: Verify that the AI agent performs as expected, responding correctly to both common and complex queries.

Usability Testing: Involve real users to test the agent’s responses and conversational flow, identifying potential areas for improvement.

Performance Testing: Evaluate the agent’s ability to handle a high volume of interactions without lags, especially during peak times.

Fallback Mechanism Testing: Confirm that the agent properly escalates issues it cannot resolve to human agents and communicates clearly when it reaches its limitations.

7. Deployment and Integration

Once tested, deploy the AI agent to your desired customer support channels. Integration is key to providing a seamless experience, enabling the agent to access data and update systems as needed.

Common Deployment Channels:

Website: Embed the AI agent directly into your website for live chat support.

Mobile App: Integrate the AI agent into your mobile app to enhance customer experience on the go.

Messaging Platforms: Deploy on platforms like WhatsApp, Facebook Messenger, or Slack to meet customers on their preferred channels.

Voice-Enabled Devices: If applicable, make the AI agent available through voice-activated assistants like Amazon Alexa or Google Assistant.

Integration Checklist:

Ensure the agent can retrieve and update customer data in real-time.

Test interactions across multiple platforms to ensure consistency.

Implement logging mechanisms to track performance and user feedback.

8. Monitoring and Optimization

Deployment is only the beginning. Monitoring the AI agent’s performance and continually optimizing it based on user interactions and feedback is essential for long-term success.

Key Metrics to Track:

Customer Satisfaction (CSAT): Measure customer satisfaction to gauge the agent’s effectiveness.

Response Accuracy: Regularly review the agent’s accuracy to ensure it provides correct responses.

Resolution Rate: Track the percentage of issues resolved by the AI agent versus those escalated to human agents.

Engagement Rate: Assess how many users interact with the AI agent and the duration of these interactions to understand engagement.

Ongoing Optimization Strategies:

Feedback Loops: Use customer feedback to refine the agent’s responses and improve accuracy.

Regular Model Retraining: Update the agent’s training data to keep up with evolving customer needs and product changes.

A/B Testing: Experiment with variations in response tone, conversation flow, and escalation options to improve user satisfaction.

9. Future Considerations: Evolving Your AI Agent

AI technology is constantly evolving, which means there are opportunities to enhance your AI agent over time:

Emotional Intelligence: Future developments in affective computing could enable AI agents to detect and respond to customer emotions, making interactions more personalized.

Proactive Support: Equip your AI agent to provide proactive assistance by notifying users about service outages, order updates, or renewal reminders.

Multilingual Support: As global reach expands, consider implementing multilingual capabilities to cater to non-English speaking customers.

Conclusion

Building an effective AI agent for customer support involves strategic planning, choosing the right technologies, designing for user experience, and ongoing improvement. By carefully defining your objectives, training the agent on quality data, and integrating it with your customer support ecosystem, you can create an AI-powered agent that enhances customer satisfaction, reduces operational costs, and scales effortlessly with your business. With the right approach, an AI agent can be an invaluable asset to your customer support strategy, delivering exceptional service and fostering lasting customer loyalty.

[tomreview]

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[loveayase]

Python - IBM Watson TTS API

1. 개요

평소에 유튜브 보�� 트위치 방송을 자주보는 편인데... 도네이션을 보면 굉장히 머리를 탁! 치게 하는 엄청난 드립들이 많이 보였다. TTS 서비스가 최초에는 남자 여자 정도밖에 없었는데, 어느새 잼민이도 나오고 기타 등등도 나오는 것으로 봥서 저거 녹음을 직접 다하는 건지.. 아니면 최근에 GAN 기반의 인공지능 모델에 목소리를 합성해서 만든건지 궁금했다.

그리고 가장 알고싶었던건 도네이션 과연 원가가 얼마인가 싶었다. 알아보니 아니나다를까 모델자체를 학습하고, 데이터가 많이 수집되어있는 곳은 구글, IBM 같은 기업이었고 구글 TTS를 사용하려다가 구글은 메뉴얼도 아주 잘되어있고 성능도 좋을 것 같고, 혹시 내가 업무에서 사용할지도 모르니까 크레딧을 아끼자는 측면에서 IBM Watson TTS를 적용해보았다.

트위치 방송에 사용되는 프로그램은 OBS Studio가 대표적인데 도네이션을 연동한다는 의미는 아래와 같다

OBS Studio의 웹페이지를 연동, 해당 웹페이지의 javascript, css 등의 코드를 통하여 구현, 일반적으로 웹페이지는 이벤트기반의 동작이기 때문에 서버로부터 이벤트를 받아서 처리하기 위해서 socket.io 연동까지가 프론트엔드 사이드

socket.io 메시지를 보내기 위한 백엔드 사이드, 및 이벤트 발생

딱 보니 저렇게 구현하면 되겠다 싶어서 직접 만들어 보았다. 아 여기서 본인이 사업화를 하고 싶다면 도네이션을 받는 사이트를 만들면되겠다. 필자는 웹프로그래밍에 지쳐 더이상은 Naver를 외치면서, 트위치 챗봇을 연동했다. 

2. 도전 해본 새로운 기술

IBM Watson TTS Service

TTS는 Text to Speech로써, 문장을 보고 사람이 읽는 듯한 음성을 만들어내는 서비스를 말한다.

ibm의 경우 한달에 10,000글자까지는 무료로 제공하고 있으며, 유료의 경우에는 한달에 1000글자당 0.02$를 청구한다.

트위치 챗봇

트위치의 채팅시스템은 20년전의 IRC시스템을 공유하고 있다. 따라서 IRC를 조금 해본 사람들이면 아 이게 비슷한데 라는 느낌을 많이 받을 것이며, 안 받는다면 트위치 채팅을 굉장히 ���스터마이징 했기 때문이라고 생각하면된다.

3. 까먹지 않기 위해 복습한 기술

는 따로 없습니다 ㅎ

4. 결과

영상편집 중

References

IBM Watson  https://cloud.ibm.com/apidocs/text-to-speech

[burningaurora]

Hey just wondering how do you make the tts fics what software do you use what format are they that sort of thing because I’m wanting to make some for myself as I sometimes find actually reading super difficult and have gotten through most the good podfics for the ships I like

I've answered this a couple times already (here), but my process has changed drastically in the last few months. For someone who isn't a software developer in real life I would recommend using Microsoft Edge or if you want actual files to output https://www.narakeet.com/ is a great simple paid option with lots of voices to choose from. For anyone who is curious and wants the extensive answer feel free to read below.

I'm going to start with saying there are probably better ways to do this, but it works fairly well for me so it's what I do.

I still use two programs to achieve my desired results. Program number 1 simply takes the html from AO3 and fixes common errors and pronunciation issues I've ran into throughout my recording. The major improvement here is that it now splits the fic apart by paragraph and by speaker. The entire paragraph and speaker concept is very generic and doesn't actually determine who is speaking each line. Below is a brief glimpse at what the file looks like

(Excerpt from A Prince's Promise by @engie-ivy)

I then go through the file and choose who speaks each line and how many milliseconds I want between them. After that I configure my app to determine who speaks which voice. (I currently integrate with Amazon Polly, Microsoft Azure TTS, Google TTS, IBM Watson, and Narakeet.) My 2nd app loops through my configured file and outputs numeric files with the narrations in the desired voices. I am able to import those files into Audacity and combine them into one large file that I distribute to the masses (not really masses a handful of delightful fanfiction listeners).

[geeksflow]

Text to Speech: Best Text to speech softwares of 2021 are speechelo, Google TTS, IBM TTS and Natural Readers TTS. In this video I also covered how to use Text to speech software to get YouTube Monetization. 

Speechelo (HIGHLY RECOMMENDED): http://bit.ly/SPEECHELO-OFFER

Text to Speech by Google: https://cloud.google.com/text-to-speech

Text to Speech by IBM: https://www.ibm.com/demos/live/tts-demo/self-service/home

Text to speech by Natural Readers: https://www.naturalreaders.com/online/

            YouTube Channel Policies: https://www.youtube.com/intl/en-GB/howyoutubeworks/policies/community-guidelines/

            Compared to voice over experts it's better to use Artificial based softwares like Speechelo, because these softwares cost efficient, time efficient, and no human interference is needed. We can use Text to Speech softwares for YouTube videos also but we need to make content that is unique, and we need to use good Text to Speech Software like Speechelo. Proper Seo (Search Engine Optimization) should be done, Your Youtube Video Content should cprovide value for your viewers and policy violation rules should be followed well only then your youtube channel is going to get monetized.

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[christipichardo-blog]

On-line Mp3 Cutter

Need to lower MP3 information? AMR to WAV, MP3, OGG, AAC, FLAC, MPC, MMF, AU, AIFF, QCP. When using IBM Watson Speech to Textual content (STT) and Text to Speech (TTS) providers for my Cognitive Candy challenge I started off using WAV file format. That was the easy alternative since WAV is a uncooked audio format requiring no further software for encoding. Support for Cover Artwork Obtain and add album covers to your files and make your library much more shiny. Now let's have a look on the steps to convert the file. How one can convert the WAV file to Ogg format. Ok, so we are going to follow a step by step course of. With so many media formats accessible at the moment, odds are it's worthwhile to convert recordsdata from one format to a different quite ceaselessly. There are 4 methods so that you can choose your files - Kind Laptop, URL, Google Drive or convert wav to ogg Dropbox. Add your files according to your recordsdata type. has a recording perform that lets you record from line-in (cassette, LP, and many others.) streaming audio, or some other supply out there in your systemUse the audio recording feature to file MIDI ,audio file protected by DRM to another audio format:mp3,wav,wma. I like this little board I'm utilizing it for two initiatives. I purchased 2 and one is for my Chewbacca costume the other for Darth Vader. I used to be able to assign sounds to buttons to play separate recordsdata.

Click on on Format" after which merely select MP3". Open iSkysoft iMedia Converter Deluxe program and click on on Add Files" button on the dwelling screen. Choose all of the WAV files that you need to convert. It's also possible to add a folder of WAV information to this system with out trouble. Extra convenient, you'll be able to straight drag the WAV information to it. Convert recordsdata from wav to ogg,MP2, WAV, WMA, AAC, APE, FLAC, WV, TTA ,SPX,MPC,wav and MP4 to WAV and backwards. sixteen Opera Mini itself would not assist any video or audio, however any video or audio is handed to the machine to play if it has help for that format. Opera Cellular also does this with unsupported codecs. Convert m4a to mp3, wav, aac, wma and ogg. As a substitute of compressing the whole file and risking dropping its quality, you possibly can trim the audio file to make it smaller. convert wav to ogg an audio or music file to the WAV format utilizing our free on-line WAV audio converter. Add your sound file or provide us with a URL to the file and the conversion will begin straight after. You can extract audio from the media file and converted to WAV should you add a video file.Super is a extremely popular and free audio converter. You may be shocked on the long checklist of audio formats it supports. When you have an audio file recorded in a rare format and also you need it converted to a more frequent format, you must check out the Tremendous audio converter. Input formats embrace MP3, MP2, WMA, WAV, WV, TTA, RM, RAM, OGG, MPP, M4A, FLAC, MMF, APE, AAC, AMR, and AC3.The goal of FF Multi Converter is to gather all multimedia types in a single application and supply conversions for them simply via a person-pleasant interface. Extra choices might be gradually added. Moreover, you'll be able to allow Alt WAV MP3 WMA OGG Converter to save the folder construction, overwrite duplicate files, add a suffix to the duplicate files or to rename the unique tracks.MP3's bitrates vary from 8kbps to 320kbps. A typical MP3 file encoded at 128kbps is near CD high quality. MP3 audio is more and more being used in video production coupled with varied MPEG4 video codecs like divx. VLC media participant will let you've got a player and a converter. Nonetheless, it's apparent that this tool isn't as easy to make use of as we expect. And it crashes typically.Along with converting single audio information into different formats in bulk, you can join multiple files into one larger audio recordsdata with Freemake Audio Converter. You too can alter the output high quality before converting recordsdata. A: It is easy! Just click on the WAV to OGG Converter download button at the page. Clicking this link will begin the installer to download WAV to OGG Converter free for Windows.

[createaivoiceovers]

Generate Better Audio Content with Quick Turnaround

Content that requires the human voice, such as videos, podcasts, audio ads, and online courses, is getting more popular and more engaging than text or images alone. This presents businesses, content creators, and marketers with a challenge: finding voices for all this audio material. Artificial voices have been around for some time, but the results were not very impressive.

AI voiceover technology has been rapidly advancing, giving you the ability to create human-sounding voices for any purpose. This can be a powerful way to create more videos and audio presentations without having to do the voiceover yourself or hire someone else to speak for you. To give you an idea of what’s available, check our Voice and Music Libraries.

Text to Speech Generator (TTS) audio using createAIvoiceovers.com Online Text to Voice Generator with high-resolution audio synchronization. Our Voice Library is stocked with the best synthetic voices from Google TTS, Amazon-Polly, IBM Watson & Microsoft Azure. Quickly convert your text in to natural-sounding speech and instantly download as MP3 audio files.

createAIvoiceovers.com is an online audio conversion Text to Speech Online system that harnesses the latest synthetic speech technology to create a high-quality AI voice that more accurately mimics the pitch, tone, and pace of a real human voice. The AI voice enables users to realize substantial cost and time reduction versus traditional audio production methods.

Our process of text-to-speech helps users address the challenges of delivering their content and marketing messages to a wide array of audiences.

The concept of Text to Speech is not new, but its application has become far more life-like versus it’s early robotic sounding voice renderings. The latest natural voice sounding technology allows any digital material to have its own voice regardless of the medium (eLearning, marketing, blogging, advertising, corporate communications, electronic gaming, audiobooks, website). The text-to-speech technology is a winner solution to those visually impaired, and those challenged with reading disabilities.

createAIvoiceovers.com is owned and operated by The Seaplace Group, LLC of Sarasota, Florida.

[alabamaonline]

Speech to text android

For text to speech, however, the process is more involved, as not only does the speech engine have to be taken into account, but also the languages available and installed from the Text To. Since its inception, Android has been able to recognize speech and output it as text. Head to the Settings app, tap “System,” then “Languages & input,” and “On-screen keyboard.” On this page, tap “Manage on-screen keyboards,” then toggle “Google Voice Typing ” to off. This article covers the basics of using the very powerful Android.Speech namespace. Thankfully, it’s fairly easy to remove the duplicate. The app will then analyze the text and use it as a command to. Until the transition is complete, those who are using Android 12 Developer Preview 3 - and presumably the upcoming Android 12 Beta - will have two listings for Google Voice Typing by default. In this tutorial I will show you how to create a simple Android App that listens to the speech of a user and converts it to text. In that update, Google has included Android 12 specific code to rename the app from “Google Text-to-speech” to just “Google Speech.” This new name change better reflects that the app handles both text-to-speech as well as speech-to-text. More specifically, that app has gotten an update to version 26 that is currently only available through Android 12 Developer Preview 3 and hasn’t rolled out through the Play Store. There is a catch though - the device will require Google Search app for the service to work. Next, we found that the newer listing of Google Voice Typing is coming from the Google Text-to-speech app. For Speech-to-text, Android provides an Intent based API which launches Googles Speech Recognition service and returns back the text result to you. This points to Google Voice Typing being removed from Google Search in the near future, but presumably only on Android 12+ devices. ” With a bit of investigation from our APK Insight team, we’ve found the underlying cause for the change.įirst, in the latest beta version of the Google Search app, we’ve found that they’ve included code to rename the Voice Typing keyboard to add “,” but only on Android 12. This starts the speech recognition activity, and you can then handle the result in. Xamarin Community Toolkit - MediaElement - Code Samples. The TextToSpeech class in Xamarin.Essentials enables an application utilize the built in text-to-speech engines to speak back text from the device and also to query available languages that the engine can support. Pretty sure its the latter - Android, as it affects all the apps. Xamarin.Essentials: Text-to-Speech - Xamarin.

Im not sure if its a Google thing, a Verizon thing, a Samsung thing, an Android thing, or what. In your app, call startActivityForResult () using the ACTIONRECOGNIZESPEECH action. A couple of months ago something changed - there was some software update that really made the speech-to-text function a lot worse. Use speech input to send messages or perform searches. Distraction-free, Fast, Easy to Use & Free Web App for Dictation. Call the system's built-in Speech Recognizer activity to get speech input from users. To access it, simply switch keyboards - usually done by long-pressing spacebar or with a dedicated button in the bottom navigation area - and choose “Google Voice Typing.”Īs spotted by one of our readers, those on Android 12 Developer Preview 3 now have two options in this list, “Google Voice Typing” and “Google Voice Typing. The Professional Speech Recognition Text Editor. Create an IBM Cloud Account Enable the Speech to Text service and obtain your API Key Add the IBM Watson SDK to your Android project with Gradle Request. A feature available from Android 1. Up to now, Google Voice Typing has been included in Android as part of the core Google Search app. Android OS provides an awesome feature called TTS i.e (Text To Speech) and STT i.e (Speech To Text). This is due to a mildly interesting tweak being made that moves Google Voice Typing from one app to another. Finally, we decided which providers were best suited for what our readers need.Those on the Android 12 Developer Preview have begun to notice a “Google Voice Typing ” option in their keyboard list.

Next, we took a closer look at several factors, including the price, free trial options, accuracy rates, and more. To find the best voice-to-text apps we compiled a list of the most popular options available.

[hunterrevolution940]

Best Tts Voices

The Best & Most Realistic Text to Speech AI Voices We leverage only the best text to speech voices from Google Wavenet, Amazon Polly, IBM Watson and Microsoft to generate accurate and realistic speech. Choose from a growing library of 570+ natural sounding AI voices across 55+ languages to convert text to voice. Acapela Group Virtual Speaker is an example of the best Text to Speech software in the market. With more than 70 voices in 30+ languages, this software is a bomb. In addition to these, you can also add emotions like sad, happy, joy, etc., in the speech. The Virtual Speaker can be regulated with various frequencies.

Voice Dream Reader. Or, jump to: Best free text-to-speech apps. While traditionally this has been in the realm of professional dictation and transcription. Our text to speech technology has benefited end-users, enterprises, hardware and software developers. Click on the image to view some indicative applications of Text-to-Speech technology. Today, 07/07/17 we’re announcing that after 10+ years of helping our customers utilize best-in-class synthetic voices, we will be discontinuing INNOETICS.

Have you ever heard about Artificial intelligence (AI)? According to Wikipedia, it is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals.

Talk-With-AI is a free Text To Speech (TTS) developed by ADCREW LLC. What can “Talk-With-AI” do for Content Creators? Magnesium atomic number. In this paragraph, we are going to talk about why the truly Content Creators should use it for their business. Here is the list of its incredible benefits you should know:

VOICE OVER

Best Tts Spam

Create your own voice in dozen of languages by yourself with just 1 click!

Imagine you are a marketer and your client is asking you to pick a voice for their production, sometimes in foreign languages, within a minute. How can you do that, tell me! Using the TTS service in this hard situation is the best choice to beat all competitors. No pain, still gain!

AUDIOBOOKS

Best Tts Voice

Making audiobooks to sell on the Internet!

A voilà!

Making money online is an attractive idea! You can make your content to sell, and one of them is creating audiobook to sell. However, you can’t just keep on speaking and speaking for the whole day in your life to make audiobooks with your throat hoarse. You might think about hiring someone else to do it for you? Hmm, hiring means paying money for future investment in a long wait, sometimes, it makes you regret.

Do you ever talk to me “Not if I can help it”? Using Talk-With-AI can help it! Just 1 click, your speech is ready! Free!

VOICES FOR BUSINESS

You can create professional voices for your business telephone system.

A lot of enterprises are using automated services with natural voices for their business. It cuts the cost of human resources and increases profit and speed (I know, it is not good news for everyone). With the dynamic, flexible, and adaptive modern business, the entrepreneurs have the reason to use AI Text To Speech service for their business nowadays.

LEARNING LANGUAGES

This TTS tool allows you to listen to the natural voices of any text aloud.

My mother language is not English, that is the fact! So take it or leave it, I have to learn English on my own. The hardest part of this learning is the pronunciation. As a result, if you are not good at pronunciation, you are not good at listening, too.

Finding a native speaking partner to ask him/her to speak to/with you may be another pain you are suffering. Meanwhile, you can give Talk-With-AI a try! As a result, you are also giving you a chance to listen to the NATIVE VOICE from most languages in the world.

And Many More!

All the voices in this video bellow were created by #TalkWithAI.

#adcrew #adcrewllc #intelligence#tts#talkwithai#powertools#business#storytelling#ai#learning#socialmedia#marketing#youtube#podcasting#video#speech#content#podcasts#digitalmarketing#speechrecognition#podcast

Hey You! Welcome to my channel!

A Novel Endovascular Therapy for CSF Hypotension Secondary to CSF-Venous Fistulas

Thầy Robert Trần & Cộng Sự

This is the AI Text To Speech Offer!

[cybersecurityict]

AI Voice Cloning Market Size, Share, Analysis, Forecast, Growth 2032: Ethical and Regulatory Considerations

The AI Voice Cloning Market was valued at USD 1.9 Billion in 2023 and is expected to reach USD 15.7 Billion by 2032, growing at a CAGR of 26.74% from 2024-2032.

AI Voice Cloning Market is rapidly reshaping the global communication and media landscape, unlocking new levels of personalization, automation, and accessibility. With breakthroughs in deep learning and neural networks, businesses across industries—from entertainment to customer service—are leveraging synthetic voice technologies to enhance user engagement and reduce operational costs. The adoption of AI voice cloning is not just a technological leap but a strategic asset in redefining how brands communicate with consumers in real time.

AI Voice Cloning Market is gaining momentum as ethical concerns and regulatory standards gradually align with its growing adoption. Innovations in zero-shot learning and multilingual voice synthesis are pushing the boundaries of what’s possible, allowing voice clones to closely mimic tone, emotion, and linguistic nuances. As industries continue to explore voice-first strategies, AI-generated speech is transitioning from novelty to necessity, providing solutions for content localization, virtual assistants, and interactive media experiences.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/5923 

Market Keyplayers:

Amazon Web Services (AWS) – Amazon Polly

Google – Google Cloud Text-to-Speech

Microsoft – Azure AI Speech

IBM – Watson Text to Speech

Meta (Facebook AI) – Voicebox

NVIDIA – Riva Speech AI

OpenAI – Voice Engine

Sonantic (Acquired by Spotify) – Sonantic Voice

iSpeech – iSpeech TTS

Resemble AI – Resemble Voice Cloning

ElevenLabs – Eleven Multilingual AI Voices

Veritone – Veritone Voice

Descript – Overdub

Cepstral – Cepstral Voices

Acapela Group – Acapela TTS Voices

Market Analysis The AI Voice Cloning Market is undergoing rapid evolution, driven by increasing demand for hyper-realistic voice interfaces, expansion of virtual content, and the proliferation of voice-enabled devices. Enterprises are investing heavily in AI-driven speech synthesis tools to offer scalable and cost-effective communication alternatives. Competitive dynamics are intensifying as startups and tech giants alike race to refine voice cloning capabilities, with a strong focus on realism, latency reduction, and ethical deployment. Use cases are expanding beyond consumer applications to include accessibility tools, personalized learning, digital storytelling, and more.

Market Trends

Growing integration of AI voice cloning in personalized marketing and customer service

Emergence of ethical voice synthesis standards to counter misuse and deepfake threats

Advancements in zero-shot and few-shot voice learning models for broader user adaptation

Use of cloned voices in gaming, film dubbing, and audiobook narration

Rise in demand for voice-enabled assistants and AI-driven content creators

Expanding language capabilities and emotional expressiveness in cloned speech

Shift toward decentralized voice datasets to ensure privacy and consent compliance

AI voice cloning supporting accessibility features for visually impaired users

Market Scope The scope of the AI Voice Cloning Market spans a broad array of applications across entertainment, healthcare, education, e-commerce, media production, and enterprise communication. Its versatility enables brands to deliver authentic voice experiences at scale while preserving the unique voice identity of individuals and characters. The market encompasses software platforms, APIs, SDKs, and fully integrated solutions tailored for developers, content creators, and corporations. Regional growth is being driven by widespread digital transformation and increased language localization demands in emerging markets.

Market Forecast Over the coming years, the AI Voice Cloning Market is expected to experience exponential growth fueled by innovations in neural speech synthesis and rising enterprise adoption. Enhanced computing power, real-time processing, and cloud-based voice generation will enable rapid deployment across digital platforms. As regulatory frameworks mature, ethical voice cloning will become a cornerstone in brand communication and media personalization. The future holds significant potential for AI-generated voices to become indistinguishable from human ones, ushering in new possibilities for immersive and interactive user experiences across sectors.

Access Complete Report: https://www.snsinsider.com/reports/ai-voice-cloning-market-5923 

Conclusion AI voice cloning is no longer a futuristic concept—it's today’s reality, powering a silent revolution in digital interaction. As it continues to mature, it promises to transform not just how we hear technology but how we relate to it. Organizations embracing this innovation will stand at the forefront of a new era of voice-centric engagement, where authenticity, scalability, and creativity converge. The AI Voice Cloning Market is not just evolving—it’s amplifying the voice of the future.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[mellowfartpost]

IBM Watson Services Market is Likely to Deliver Dynamic Progression during the Period 2020 to 2025

The Global IBM Watson Services Market report offers industry overview including definitions, applications, classifications, and chain structure. The report provides a comprehensive assessment of the studied market, including key trends, historic data, current market scenario, opportunities, growth drivers, potential roadmap, and strategies of the market players.  The report further includes regional analysis to evaluate the global presence of IBM Watson Services Market.

In order to simplify the industry analysis and forecast estimation for the IBM Watson Services Market, our research report delivers well-defined market scope and systematically developed research methodology.

Get the inside scoop of the Sample report For FREE:https://www.kdmarketinsights.com/sample/35

IBM WATSON SERVICES MARKET SEGMENTATION:

By Services:

Watson Studio

Watson Knowledge Catalog

Watson AI Assistant

Watson Discovery

Watson IoT Platform

Watson Speech to Text (STT)

Watson Text to Speech (TTS)

Watson Language Services

Watson Visual Recognition

Watson Tone Analyzer

Watson Personality Insights

Watson Data Refinery

Watson Machine Learning

Watson Deep Learning

Watson Compare and Comply

Other Services

By End User Industry:

Healthcare

BFSI

Retail

Discrete & Process Manufacturing

Telecom

Media & Entertainment

Transportation & Logistics

Government

Travel & Tourism

Education

Others

Regional Analysis:

The global IBM Watson Services Market is segmented as The regional segmentation of the market includes

North America

Europe

Asia Pacific

Latin America

Middle East & Africa

The Following are the Key Features of Global IBM Watson Services Market Report:

Market Overview, Industry Development, Market Maturity, PESTLE Analysis, Value Chain Analysis

Growth Drivers and Barriers, Market Trends & Market Opportunities

Porter’s Five Forces Analysis & Trade Analysis

Market Forecast Analysis for 2020-2025

Market Segments by Geographies and Countries

Market Segment Trend and Forecast

Market Analysis and Recommendations

Price Analysis

Key Market Driving Factors

IBM WATSON SERVICES Market Company Analysis: Company Market Share & Market Positioning, Company Profiling, Recent Industry Developments etc.

Request For Customization –https://www.kdmarketinsights.com/custom/35

Key Players:

This section of the report includes a precise analysis of major players with company profile, market value, and SWOT analysis. The report also includes manufacturing cost analysis, raw materials analysis, key suppliers of the product, mergers & acquisitions, expansion, etc. Following companies are assessed in the report:

KPMG International Limited

Capgemini SE

Tata Consultancy Services Limited

Wipro Limited

IBM Corporation

Datamato Technologies Private Ltd.

Mainline Information Systems Inc.

DXC Technology Limited Accenture Plc

Deloitte Touche Tohmatsu Ltd.

Tech Mahindra limited

Infosys Limited

HCL Limited

Other Players

Why KD Market Insights?

We use latest market research tools and techniques to authenticate the statistical numbers

Availability of customized reports

Expert and experienced research analysts in terms of market research approaches

Quick and timely customer support for domestic as well as international clients

Request For Discount –https://www.kdmarketinsights.com/discount/35

About Us:

KD Market Insights offers a comprehensive database of syndicated research studies, customized reports, and consulting services. These reports are created to help in making smart, instant, and crucial decisions based on extensive and in-depth quantitative information, supported by extensive analysis and industry insights.

Our dedicated in-house team ensures the reports satisfy the requirement of the client. We aim at providing value service to our clients. Our reports are backed by extensive industry coverage and is made sure to give importance to the specific needs of our clients. The main idea is to enable our clients to make an informed decision, by keeping them and ourselves up to date with the latest trends in the market.

Contact Us:

KD Market Insights

150 State Street, Albany,

New York, USA 12207

+1 (518) 300-1215

Email: sales@kdmarketinsights.com

Website: www.kdmarketinsights.com

[eurekakinginc]

Posted by ideanusx via /r/artificial. Join Discussion: http://ift.tt/2tWlvtY. Curated by: www.eurekaking.com

[jennabrileyus]

i6net

VoiceXML for everybusiness | www.i6net.com I6NET provides a VoiceXML browser for Asterisk : Voximal (formerly VXI*) :

Products

VoiceXML Browser for Asterisk Voximal

The Voximal VoiceXML browser for Asterisk® gives operators and solution providers the ability to rapidly develop and deploy innovative voice and video applications via IP, PSTN, and 3G-324M networks. Voximal is fully compliant with the W3C's VoiceXML 2.0+ specification and is integrated with automatic speech recognition (ASR) and text-to-speech (TTS) software to enable advanced voice and video solutions, and real-time video calling applications. Voximal can be installed in common hardware configurations, providing a highly scalable base system to meet all customers' business and technical VoiceXML requirements. Voximal VoiceXML interpreter works directly with the Asterisk® PBX software supported by Digium®. Not only can users of the open source PBX run VoiceXML applications in the same server, they can now offer these powerful, scalable IVR / IVVR solutions at an affordable cost. Written in C, Linux Operating System, License Commercial

Key features and benefits

VoiceXML V2.0/V2.1 compliant

CCXML replaced by Call Control functions of Asterisk

Base on OpenVXI voice browser template

Application for Asterisk PBX (app_vxml)

VoiceXML accounts managment configuration (for hosting services)

Support plugging objects with the VoiceXML tag, SDK with API available

Fax support (send and receive)

Video silence parameter with VoiceXML syntax

Text-to-Speech (TTS) connector included

Automatic-Speech-Recognition (ASR) connector included

Text-to-Video (TTV) with HTTP connector (option)

Voice-Silent Detection (VSD)

MRCP v1 and v2 thru uniMRCP for TTS and ASR.

Cloud Ready:

We offer Amazon, Azure and Docker virtual images

Amazon Polly and Lexa

Azure Cognitive Services (TTS and STT)

Google TTS and STT Apis

IBM Watson

Text-to-Speech engines supported:

Flite - free (TTS) from CMU Speech Group

Voxygen (TTS)

Cepstral (TTS)

Verbio (TTS)

Nuance Scansoft (TTS)

Acapela (TTS)

Universal HTTP connector for any TTS engines

Universal MRCP connector for any TTS engines (uniMRCP)

Automatic-Speech-Recognition engines supported:

Lumenvox Speech Engine (ASR)

Verbio Speech Server (ASR)

VoiceInteraction Speech Engine (ASR)

Vestec Speech Engine (ASR)

Loquendo Speech (ASR-MRCP)

Nuance Speech (ASR-MRCP)

PocketSphinx (SpeechToText)

universal MRCP v1 and v2 (ASR) (uniMRCP modified with extra features)

Asterisk requirements:

Asterisk 1.8 / 11 / 13 / 14

Distributions: Debian, CentOS, Ubuntu, Raspbian from Updates & News http://www.voip-info.org/wiki/view/i6net

[ipadsadvise]

IBM Inks VMware, GitHub, Bitly Deals, Expands Apple Swift Use As It Doubles Down On The Cloud

While a big component of the mobile industry rolls around the roads of Barcelona, IBM is playing host at its own big InterConnect occasion in Sin city, where it revealed a rush of offers that highlight one more significant facet of the growth of mobile: the surge of cloud solutions. Today, IBM introduced further collaborations with Apple, VMware, GitHub, Bitly as well as Siemens.

Separately, IBM also made some significant cloud statements of its own covering software program, Watson APIs and app advancement using a new platform, Bluemix OpenWhisk, as Huge Blue remains to grab new-wave profits to counter decreases in its heritage business.

Apple: IBM has been collaborating with Apple given that 2014 on creating organization movement options with each other, however today's news focuses much more on programmer devices, specifically Apple's computer programming language Swift and also IBM's duty in making it accessible in the cloud. This initial started in December, when IBM announced its Swift Sandbox after Apple open sourced Swift, making it the first cloud carrier to make it possible for application growth in Swift. That Sandbox is now used by over 100,000 designers as well as over half a million code runs, IBM claimed today. And also now IBM is bringing this along with its bigger enterprise have fun with Apple, with preview of a Swift runtime and a Swift Bundle Catalog to produce venture apps.

"By bringing Swift beyond the client to the web server, IBM is damaging down barriers between front-end as well as back-end growth, which could provide enterprises a single language to build rich experiences and also back-end company logic," the company states. This, IBM proceeds, boosts development rate and supplies a more safe toolchain for end-to-end application development.

VMware. This offer is a move by IBM to extend right into even more hybrid cloud solutions, yet also maybe an action by VMware to extend additionally in its cloud solutions partnerships with other events in the wake of other developments, specifically regarding EMC.

IBM states that enterprises that utilize VMware technologies-- which covers virtually 100 % of the Ton of money 100-- can now run services on 45 IBM Cloud Information Centers internationally in a seamless fashion. Services covered, IBM states, consist of pre-configured VMware SDDC atmospheres-- VMware vSphere, NSX as well as Virtual SAN on the IBM Cloud, and IBM will certainly additionally now develop and market new hybrid cloud solutions covering workload migrations, calamity recovery, capability development and also information establishment consolidation.

As with Apple, IBM collaborating with VMware is not completely new. "This collaboration, an extension of our 14-year plus relationship with IBM, shows a shared vision that will certainly assist organization consumers quicker as well as effortlessly welcome the hybrid cloud," stated Rub Gelsinger, CEO of VMware.

However, this was generally a reseller contract up to now. Today's news is the first tactical partnership in between VMware and IBM Cloud. "This collaboration allows both sides to sell and visit market with each other with a mixed remedy. On the item side, this collaboration allows us to supply the complete pile of administration tooling as a solution in SoftLayer. We've had tactical connections around marketing VMWare software program for years. This is a critical collaboration with joint advancement and go-to-market internationally," Damion Heredia, VP of Cloud System & Product Management at IBM, told TechCrunch.

Other partnerships announced today include a GitHub deal, in which IBM will provide a dedicated GitHub Enterprise experience using its Bluemix cloud platform, preparing for joint coding. As well as Bitly said that it would be shifting 25 billion web links made by way of its web link reducing solution to IBM's cloud. And also finally, Siemens as well as IBM stated they will interact on energy performance solutions that will certainly bring together IBM's IoT knowledge with Siemens energy and also sustainability platform.

Aside from these collaborations, IBM today likewise revealed some advancements of its very own on the cloud front.

This consisted of a brand-new collection of solutions that IBM is calling its Cloud Connectors, enabling designers to much more easily connect services in the cloud, "whether they are on the cloud or otherwise." These include WebSphere Connect, API Connect, MQ Link, DataWorks, z/OS Connect Organization Version, and also WebSphere Blockchain Attach.

The company additionally placed 3 brand-new Watson expert system APIs right into beta-- Tone Analyzer, Emotion Analysis and Visual Recognition — are currently available in beta, and it has actually increased the existing Text to Speech API with emotion as well as re-releasing it as "Meaningful TTS". If you have actually seen demos of IBM's Pepper robotic, you could see some of the company's ambitions to include even more empathy as well as feeling to machines to make them a lot more human-like, and also this is a continuing advancement on that particular front.

Finally, IBM is additionally attempting to produce a much more streamlined atmosphere for application growth-- as well as especially event reactions-- with the launch of IBM Bluemix OpenWhisk. This is really much a part of IBM's Internet of Things play: examples of microservices that would certainly be included on this channel include computer mouse clicks or sensing unit information from a video camera: when an occasion takes place, IBM claims, the code is performed. "Developers need not fret about points like pre-provisioning facilities, such as servers or procedures – they can simply concentrate on code, significantly accelerating the process." IBM claims any custom-made code put in a Docker container can be run.

None of the above information included information concerning rates. As we have explained in the past, the company has actually seen 15 straight quarters of profits decrease now, and while sales in new locations like cloud continue to grow, it's not yet sufficient to balance out declines in its larger legacy business around web servers and also on-premise solutions. Whether that indicates that longer term, Large Blue might end up being even more of, well, a Tool Blue, for currently the business is much too big not to matter. It's partnering with many other business as well as introducing solutions of its own are signs of just how it is firing on all cyndrical tubes to turn the ship and also bring its IT dealflow with it.