VibeVoice

Active
GitHub Python MIT

Description

Open-source frontier voice AI from Microsoft, providing high-quality speech synthesis and recognition for building real-time conversational voice agent applications.

Key Features

  • 60-minute single-pass ASR — Processes up to 60 minutes of continuous audio in one pass with consistent speaker tracking throughout
  • Structured transcription output — Jointly produces speaker identity, timestamps, and content (Who/When/What) without post-processing
  • Custom hotword guidance — Accepts domain-specific terms and proper nouns to significantly improve recognition accuracy on specialized content
  • 90-minute multi-speaker TTS — Synthesizes up to 90 minutes of conversational speech with up to 4 distinct speakers
  • Continuous speech tokenizers — Uses Acoustic and Semantic tokenizers at 7.5Hz ultra-low frame rate for efficient long-sequence processing
  • Real-time streaming TTS — Supports streaming text input and real-time speech generation for conversational agent applications

Use Cases

💡 Meeting transcription: Automatically convert hour-long meeting recordings into labeled transcripts with speaker identification and timestamps
💡 Podcast and audiobook generation: Use multi-speaker TTS to synthesize long-form conversational podcasts or audiobook content
💡 Real-time voice agent building: Construct AI agents with real-time voice interaction using streaming TTS and ASR capabilities
💡 Multilingual speech recognition: Process long audio in 50+ languages for multinational meetings and multilingual content

Strengths & Limitations

Strengths

  • Actively maintained, recent updates
  • High community interest (53.6k stars)
  • Permissive open-source license (MIT)
  • Responsive to issues, low backlog

Categories

Quick Start

# Install dependencies
pip install torch torchaudio
pip install git+https://github.com/microsoft/VibeVoice.git

# ASR transcription example
from vibevoice.asr import VibeVoiceASR

model = VibeVoiceASR.from_pretrained("microsoft/VibeVoice-ASR")
result = model.transcribe("meeting_recording.wav")
print(result.text)

Related Projects

Langchain-Chatchat

38.6k · Python
Stale B

A local knowledge base RAG and Agent application platform built on Langchain with support for ChatGLM, Qwen, Llama and other LLMs, offering conversation, knowledge base management, and agent capabilities.

ragllmpython +3
  • · Local knowledge base QA — Document loading, text splitting, vectorization and semantic retrieval via Langchain with BM25+KNN hybrid search
  • · Multi-framework model inference — Supports Xinference, Ollama, FastChat, LocalAI for GLM-4, Qwen2, Llama3 and more
  • · Agent tool calling — Optimized for ChatGLM3/Qwen with auto tool selection, single tool parameter parsing, and multimodal image chat

LangBot

17.6k · Python
Active A+

Production-grade platform for building agentic IM bots supporting Discord, Slack, LINE, Telegram, WeChat, Feishu, DingTalk, QQ, and more with Agent orchestration, knowledge base, and plugin system.

chatbotagentpython +2
  • · Supports 10+ IM platforms including Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Feishu, DingTalk
  • · Built-in agent orchestration, tool calling, multimodal support, streaming output, and RAG knowledge base
  • · Deep integration with Dify, Coze, n8n, Langflow and other major LLMOps platforms

infiAgent

1.2k · Python
Normal B

Build your own Cowork, AI Scientist and other SoTA Agents just by editing config files. Support anthropic skills. An infinite-horizon agent framework designed for long-running, complex tasks.

agentframeworksdk +4
  • · Supports unlimited-duration complex tasks running for days without context accumulation or compression degradation, with full recovery via Resume on any interruption
  • · Compatible with the Agent Skills open standard — drop skill folders into the library for automatic discovery, loading, and execution by agents
  • · Flexible agent architecture: multi-level hierarchy (tree-structured orchestration for complex domain tasks) and flat architecture (single agent for general tasks)

Related Articles