sherpa
1.3
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k2-fsa/sherpa

  • sherpa

k2-fsa/sherpa-ncnn

  • sherpa-ncnn

k2-fsa/sherpa-onnx

  • sherpa-onnx
    • Tutorials
    • Installation
    • Frequently Asked Question (FAQs)
    • Python
      • Install the Python Package
      • Decode files
      • Real-time speech recognition from a microphone
      • Speech recognition from URLs
      • Streaming WebSocket Server
      • Non-Streaming WebSocket Server
    • C API
    • Java API
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    • Keyword spotting
    • Punctuation
    • Audio tagging
    • Spoken language identification
    • VAD
    • Pre-trained models
    • Moonshine
    • SenseVoice
    • FireRedAsr
    • Dolphin
    • Speaker Diarization
    • Speaker Identification
    • Speech enhancement
    • rknn
    • Text-to-speech (TTS)

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Python

In this section, we describe how to install the Python package sherpa-onnx.

  • Install the Python Package
    • Method 1 (From pre-compiled wheels, CPU only)
    • Method 2 (From pre-compiled wheels, CPU + CUDA)
    • Method 3 (From source)
    • Method 4 (For developers)
    • Check your installation
  • Decode files
    • Streaming zipformer
    • Non-streaming zipformer
    • Non-streaming paraformer
  • Real-time speech recognition from a microphone
    • With endpoint detection
    • Without endpoint detection
  • Speech recognition from URLs
    • Decode a URL
    • RTMP
      • Install the server
      • Start the server
      • Start ffmpeg to push audio stream
      • Start sherpa-onnx to pull audio stream
  • Streaming WebSocket Server
    • Start the server
      • Use Python API
        • Send a file for decoding
        • Send audio samples from a microphone for decoding
      • Use a browser
    • colab
  • Non-Streaming WebSocket Server
    • Non-streaming transducer
      • Start the server
      • Start the client
    • Non-streaming paraformer
      • Start the server
      • Start the client
    • Non-streaming CTC model from NeMo
      • Start the server
      • Start the client
    • Non-streaming Whisper tiny.en
      • Start the server
      • Start the client
    • colab
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