innnky/emotional-vits

Health v2 · maintenance only

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1392 stars · 170 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Emotional VITS is a voice synthesis (TTS) model based on VITS that enables emotion-controllable speech generation without requiring manual emotion labels in the training dataset. It extracts emotion embeddings from audio using a pretrained emotion extraction model and feeds them into a modified TextEncoder, allowing inference with a reference audio to control the emotional tone of synthesized speech.

Use cases

• synthesize speech with controllable emotion from a reference audio clip
• train an emotional TTS model on a dataset without emotion annotations
• cluster audio files by emotional similarity to pick reference clips
• fine-tune an existing VITS checkpoint to add emotion control
• build multi-speaker TTS with per-speaker emotional expression

When to avoid

• you need text-driven emotion control using words like 'excited' or 'calm' without providing a reference audio
• you need a production-ready TTS service with an API out of the box
• you cannot provide a reference audio clip at inference time
• you need real-time low-latency synthesis on constrained hardware

Facets

library · maturity maintenance

tts speech-recognition machine-learning deep-learning audio-processing speech-processing machine-learning python cross-platform vits emotional-tts voice-synthesis emotion-embedding speech-synthesis jupyter-notebook audio natural-language-processing

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markdown · JSON · MCP: product_card(name="innnky/emotional-vits")