Auto Added by WPeMatico
IBM released two new open speech recognition models— Granite Speech 4.1 2B and Granite Speech 4.1 2B-NAR — and they make a compelling case for what a ~2B-parameter speech model can do. Both are available on Hugging Face under the Apache 2.0 license. The pair targets a specific problem that enterprise AI teams know well: […]
Elon Musk’s AI company xAI has launched two standalone audio APIs — a Speech-to-Text (STT) API and a Text-to-Speech (TTS) API — both built on the same infrastructure that powers Grok Voice on mobile apps, Tesla vehicles, and Starlink customer support. The release moves xAI squarely into the competitive speech API market currently occupied by
Google has introduced Gemini 3.1 Flash TTS, a preview text-to-speech model focused on improving speech quality, expressive control, and multilingual generation. Unlike previous iterations that prioritized simple conversion, this release emphasizes natural-language audio tags, native support for more than 70 languages, and native multi-speaker dialogue. This release signals a shift from ‘black-box’ audio generation toward
In this tutorial, we explore Microsoft VibeVoice in Colab and build a complete hands-on workflow for both speech recognition and real-time speech synthesis. We set up the environment from scratch, install the required dependencies, verify support for the latest VibeVoice models, and then walk through advanced capabilities such as speaker-aware transcription, context-guided ASR, batch audio
Mistral AI has released Voxtral TTS, an open-weight text-to-speech model that marks the company’s first major move into audio generation. Following the release of its transcription and language models, Mistral is now providing the final ‘output layer’ of the audio stack, positioning itself as a direct competitor to proprietary voice APIs in the developer ecosystem.
In the landscape of enterprise AI, the bridge between unstructured audio and actionable text has often been a bottleneck of proprietary APIs and complex cascaded pipelines. Today, Cohere—a company traditionally known for its text-generation and embedding models—has officially stepped into the Automatic Speech Recognition (ASR) market with the release of their latest model ‘Cohere Transcribe‘.
IBM has released Granite 4.0 1B Speech, a compact speech-language model designed for multilingual automatic speech recognition (ASR) and bidirectional automatic speech translation (AST). The release targets enterprise and edge-style speech deployments where memory footprint, latency, and compute efficiency matter as much as raw benchmark quality. What Changed in Granite 4.0 1B Speech At the
The landscape of Text-to-Speech (TTS) is moving away from modular pipelines toward integrated Large Audio Models (LAMs). Fish Audio’s release of S2-Pro, the flagship model within the Fish Speech ecosystem, represents a shift toward open architectures capable of high-fidelity, multi-speaker synthesis with sub-150ms latency. The release provides a framework for zero-shot voice cloning and granular
Google DeepMind is pushing the boundaries of generative AI again. This time, the focus is not on text or images. It is on music. The Google team recently introduced Lyria 3, their most advanced music generation model to date. Lyria 3 represents a significant shift in how machines handle complex audio waveforms and creative intent.
Cohere AI Labs has released Tiny Aya, a family of small language models (SLMs) that redefines multilingual performance. While many models scale by increasing parameters, Tiny Aya uses a 3.35B-parameter architecture to deliver state-of-the-art translation and generation across 70 languages. The release includes 5 models: Tiny Aya Base (pretrained), Tiny Aya Global (balanced instruction-tuned), and
