license: mit
datasets:
- BharathK333/VoxMorph-Dataset
language:
- en
base_model:
- ResembleAI/chatterbox
pipeline_tag: text-to-speech
tags:
- ICASSP
- Audio-to-Audio
- Zero-shot-tts
- Voice-Morphing
- Security
papers:
- https://huggingface.co/papers/2601.20883
VoxMorph: Scalable Zero-shot Voice Identity Morphing via Disentangled Embeddings
Project Page | Paper | GitHub | Demo | Dataset
VoxMorph is a zero-shot framework that produces high-fidelity voice morphs from as little as five seconds of audio per subject without model retraining. The method disentangles vocal traits into prosody and timbre embeddings, enabling fine-grained interpolation of speaking style and identity. These embeddings are fused via Spherical Linear Interpolation (Slerp) and synthesized using an autoregressive language model coupled with a Conditional Flow Matching network.
This repository hosts the official model checkpoints for VoxMorph: Scalable Zero-shot Voice Identity Morphing via Disentangled Embeddings (ICASSP 2026). It contains the checkpoint files (s3gen.pt and t3_cfg.pt) for VoxMorph, a zero-shot TTS framework built on top of Resemble AI's frozen Chatterbox-TTS backbone.