AssemblyAI launches Universal 3.6 Pro streaming speech-to-text tuned for voice agents
Microsoft releases VibeVoice-ASR-Streaming
Microsoft releases VibeVoice-ASR-Streaming
A developer released STT-MCP, a local speech-to-text tool that enables AI agents to process speech from audio and video files. The project is hosted on GitHub and targets agent workflows needing offline transcription.
A developer released STT-MCP, a local speech-to-text tool that enables AI agents to process speech from audio and video files. The project is hosted on GitHub and targets agent workflows needing offline transcription.
Fusion-runtime is an open-source runtime for building self-hosted voice agents that combine speech-to-text, an LLM, and text-to-speech in a single process. The LLM serves as the conversational reasoning layer between transcription and speech synthesis. It targets developers who want voice agents without depending on external cloud APIs or multiple separate services.
Fusion-runtime is an open-source runtime for building self-hosted voice agents that combine speech-to-text, an LLM, and text-to-speech in a single process. The LLM serves as the conversational reasoning layer between transcription and speech synthesis. It targets developers who want voice agents without depending on external cloud APIs or multiple separate services.
StreamCore is an open-source server providing realtime voice infrastructure for AI applications. It handles the audio streaming layer so developers building LLM-powered voice agents can connect speech to models without building transport infrastructure themselves. It targets developers building voice AI products.
StreamCore is an open-source server providing realtime voice infrastructure for AI applications. It handles the audio streaming layer so developers building LLM-powered voice agents can connect speech to models without building transport infrastructure themselves. It targets developers building voice AI products.
A GitHub project called Whisper Live provides a nearly-live implementation of OpenAI's Whisper speech recognition model. The project enables real-time transcription with low latency, making it useful for live captioning and voice interfaces.
A GitHub project called Whisper Live provides a nearly-live implementation of OpenAI's Whisper speech recognition model. The project enables real-time transcription with low latency, making it useful for live captioning and voice interfaces.