Soul-AILab/SoulX-Podcast

Health v2 · maintenance only

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Adoption not part of the score

3535 stars · 457 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SoulX-Podcast is the official inference codebase for a text-to-speech model that generates long-form, multi-turn, multi-speaker podcast-style dialogic speech. It supports Mandarin, English, and several Chinese dialects with zero-shot voice cloning and paralinguistic controls like laughter and sighs.

Use cases

• generate realistic podcast audio from text scripts
• synthesize multi-speaker dialogue speech
• clone voices across Chinese dialects
• add laughter and sighs to synthesized speech
• convert long-form text into natural spoken audio
• build an AI podcast generator

When to choose

• you need long-form multi-speaker dialogic speech generation
• you need Chinese dialect support like Sichuanese or Cantonese
• you want paralinguistic realism such as laughter and breathing in TTS output
• you need zero-shot voice cloning for podcast-style content

When to avoid

• you only need simple single-phrase TTS with minimal setup
• you need languages beyond Mandarin, English, and Chinese dialects
• you lack GPU resources for model inference
• you need a production SaaS rather than an inference codebase

Facets

library · maturity active

tts speech-recognition machine-learning llm-inference speech-processing artificial-intelligence python podcast-generation voice-cloning multi-speaker-speech chinese-dialects paralinguistic-control zero-shot-tts audio natural-language-processing gpu linux

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