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What is IBM Watson Text to Speech?

IBM Watson Text to Speech enables the conversion of written text into realistic audio, thereby improving customer interaction and engagement through the use of various languages and tones. This technology enhances accessibility for people with different abilities while also offering audio solutions that help maintain focus while driving by minimizing distractions. By streamlining customer service tasks, operational efficiency is greatly improved, which leads to shorter wait times for users. As a cloud-based API, Watson Text to Speech can easily integrate with existing applications or work in conjunction with Watson Assistant to produce natural-sounding audio in a range of voices and languages. This capability allows brands to establish a unique voice, creating stronger connections with customers and ensuring they feel acknowledged in their preferred language. Furthermore, the application of this technology paves the way for innovative ways to improve user experiences, which ultimately results in enhanced customer satisfaction and loyalty over time. With the potential for personalized interactions, businesses can leverage this tool to meet the diverse needs of their audiences more effectively.

What is Qwen3-Omni?

Qwen3-Omni represents a cutting-edge multilingual omni-modal foundation model adept at processing text, images, audio, and video, and it delivers real-time responses in both written and spoken forms. It features a distinctive Thinker-Talker architecture paired with a Mixture-of-Experts (MoE) framework, employing an initial text-focused pretraining phase followed by a mixed multimodal training approach, which guarantees superior performance across all media types while maintaining high fidelity in both text and images. This advanced model supports an impressive array of 119 text languages, alongside 19 for speech input and 10 for speech output. Exhibiting remarkable capabilities, it achieves top-tier performance across 36 benchmarks in audio and audio-visual tasks, claiming open-source SOTA on 32 benchmarks and overall SOTA on 22, thus competing effectively with notable closed-source alternatives like Gemini-2.5 Pro and GPT-4o. To optimize efficiency and minimize latency in audio and video delivery, the Talker component employs a multi-codebook strategy for predicting discrete speech codecs, which streamlines the process compared to traditional, bulkier diffusion techniques. Furthermore, its remarkable versatility allows it to adapt seamlessly to a wide range of applications, making it a valuable tool in various fields. Ultimately, this model is paving the way for the future of multimodal interaction.

Media

Media

Integrations Supported

ConvNetJS
GPT-4o
Gemini 2.5 Pro
Gemini 2.5 Pro Deep Think
Gemini 3 Deep Think
IBM Cloud
IBM Watson

Integrations Supported

ConvNetJS
GPT-4o
Gemini 2.5 Pro
Gemini 2.5 Pro Deep Think
Gemini 3 Deep Think
IBM Cloud
IBM Watson

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/watson-text-to-speech

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwen.ai/blog

Categories and Features

Text to Speech

API
Adjust Speaking Rate / Pitch
Audio Optimization
Custom Lexicons
Different Voice Choices
Multi-Language Support
Synchronize Speech

Categories and Features

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