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Moshi is a speech-text foundation model and full-duplex spoken dialogue framework. It uses Mimi, a state-of-the-art streaming neural audio codec.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

  • pytorch
  • speech-processing
  • speaker-diarization
  • speech-activity-detection

High-performance GPGPU inference of OpenAI's Whisper automatic speech recognition (ASR) model

On-device wake word detection powered by deep learning

  • wake-word-detection
  • hotword
  • keyword-spotting
  • keyword-spotter

:stuck_out_tongue_closed_eyes: TensorFlowTTS: Real-Time State-of-the-art Speech Synthesis for Tensorflow 2 (supported including English, French, Korean, Chinese, German and Easy to adapt for other languages)

The Swiss Army Knife of Offline AI. Chat, see, speak, and generate images on your phone or Mac — GGUF LLMs, vision, Whisper speech-to-text, Stable Diffusion, tool calling, and local-network servers. Runs on your CPU, GPU, or NPU. No account, no API key, zero data leaves your device.

Frontier CoreML audio models in your apps — text-to-speech, speech-to-text, voice activity detection, and speaker diarization. In Swift, powered by SOTA open source.

Data manipulation and transformation for audio signal processing, powered by PyTorch

aeneas is a Python/C library and a set of tools to automagically synchronize audio and text (aka forced alignment)

  • speech
  • alignment
  • tts
  • python