When Humans Growl and Birds Speak: High-Fidelity Voice Conversion from Human to Animal and Designed Sounds

TL;DR

This paper presents a high-fidelity voice conversion method that transforms human speech into animal sounds and designed vocalizations, supporting diverse non-speech sounds at 44.1kHz with improved quality and naturalness.

Contribution

It introduces a novel preprocessing pipeline and an enhanced CVAE-based model capable of converting human voices into a wide range of non-human sounds at high audio quality.

Findings

Outperforms baselines in quality, naturalness, and similarity MOS.

Supports diverse non-human sounds at 44.1kHz.

Effective voice conversion across various non-human timbres.

Abstract

Human to non-human voice conversion (H2NH-VC) transforms human speech into animal or designed vocalizations. Unlike prior studies focused on dog-sounds and 16 or 22.05kHz audio transformation, this work addresses a broader range of non-speech sounds, including natural sounds (lion-roars, birdsongs) and designed voice (synthetic growls). To accomodate generation of diverse non-speech sounds and 44.1kHz high-quality audio transformation, we introduce a preprocessing pipeline and an improved CVAE-based H2NH-VC model, both optimized for human and non-human voices. Experimental results showed that the proposed method outperformed baselines in quality, naturalness, and similarity MOS, achieving effective voice conversion across diverse non-human timbres. Demo samples are available at https://nc-ai.github.io/speech/publications/nonhuman-vc/