The American startup Useful Sensors has launched an open-source speech recognition model called Moonshine. Moonshine is designed to process audio data more efficiently, using computational resources more economically and achieving processing speeds five times faster than OpenAI's Whisper. This new model is specifically built for real-time applications on resource-constrained hardware and features a flexible architecture. Unlike Whisper, which processes audio in fixed 30-second segments, Moonshine offers a different approach.

In the rapid advancement of artificial intelligence, an international research team is paving the way for the development of AI language models in Europe. They have launched a project called MOSEL (Massive Open-source compliant Speech data for European Languages), creating a comprehensive open-source voice dataset for the 24 official languages of the European Union. This initiative aims to promote the development of open AI language models in Europe, challenging the current dominance of English.

Alibaba recently launched the new open-source voice model Qwen2-Audio, which excels in speech recognition, translation, and audio analysis, achieving significant performance improvements. Qwen2-Audio offers a basic version and an instruction fine-tuning version, supporting multiple languages such as Chinese, Cantonese, French, English, and Japanese, facilitating sentiment analysis and translation applications. Compared to Qwen-Audio, Qwen2-Audio features comprehensive optimizations in architecture and performance, utilizing more natural language prompts during the pre-training phase.

Israeli AI company aiOla has released an open source speech recognition model named Whisper Medusa, which is based on an improved architecture design that incorporates multi-head attention mechanisms, allowing it to process speech 50% faster than OpenAI's Whisper model. Whisper Medusa makes parallel predictions of ten tokens instead of the traditional one at a time, significantly enhancing speech recognition speed while maintaining performance. Its innovative training method employs weak supervision, freezing the backbone system and utilizing...

Israeli AI startup aiOla has launched an open-source speech recognition model called Whisper-Medusa, which is 50% faster than OpenAI's Whisper. The model is built on Whisper, utilizing an innovative 'multi-head attention' architecture that allows for the prediction of more tokens at once, resulting in a significant speed increase while maintaining accuracy. Whisper-Medusa has been released on Hugging Face under the MIT License, permitting both research and commercial use.

Recently, GroqCloud quietly launched Whisper V3 Large. Give it a try now, as it's already integrated into GroqChat for everyone to experience.Developers can now leverage Whisper's voice-to-text feature along with our speed to build. Keep building! [Product Link](https://groqcloud.com) [Experience Link](https://groqchat.com)

Groq has recently launched the Whisper Large-V3 model, allowing users to utilize the API in Playground or local projects to achieve speech transcription and translation functionalities. This model supports transcription in multiple languages with extremely fast processing speed, and it can translate other languages into English.

OpenAI announced the upgraded automatic speech recognition model Whisper3 at the Developer Day. Whisper3 offers multi-language support and can quickly and accurately transcribe audio to text. OpenAI plans to make the Whisper3 API available to users.