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ESPnet

The end-to-end speech processing toolkit for ASR, TTS, speech translation, and speaker diarization.

★ 9,912 GitHub Apache-2.0 asrttsspeech-translationdiarizationpytorchspeech-recognition Speech & Audio

Overview

ESPnet is a comprehensive open-source toolkit for end-to-end speech processing. It provides state-of-the-art recipes and pretrained models for automatic speech recognition (ASR), text-to-speech (TTS), speech-to-speech translation, speaker diarization, and spoken language understanding. Built on PyTorch, it includes ESPnet2, a modern rewrite with a unified trainer, streaming support, and Hugging Face integration. ESPnet is widely used in research and industry, with hundreds of pretrained models available for quick deployment.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  espnet:
    image: espnet/espnet:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/espnet:/data

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