@inproceedings{zheng-etal-2025-voicecraft,
title = "{V}oice{C}raft-{X}: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing",
author = "Zheng, Zhisheng and
Peng, Puyuan and
Diwan, Anuj and
Huynh, Cong Phuoc and
Sun, Xiaohang and
Liu, Zhu and
Bhat, Vimal and
Harwath, David",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-main.137/",
pages = "2737--2756",
ISBN = "979-8-89176-332-6",
abstract = "We introduce VoiceCraft-X, an autoregressive neural codec language model which unifies multilingual speech editing and zero-shot text-to-speech (TTS) synthesis across 11 languages: English, Mandarin, Korean, Japanese, Spanish, French, German, Dutch, Italian, Portuguese, and Polish. VoiceCraft-X utilizes the Qwen3 large language model for phoneme-free cross-lingual text processing and a novel token reordering mechanism with time-aligned text and speech tokens to handle both tasks as a single sequence generation problem. The model generates high-quality, natural-sounding speech, seamlessly creating new audio or editing existing recordings within one framework. VoiceCraft-X shows robust performance in diverse linguistic settings, even with limited per-language data, underscoring the power of unified autoregressive approaches for advancing complex, real-world multilingual speech applications. Audio samples are available at https://zhishengzheng.com/voicecraft-x/."
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<abstract>We introduce VoiceCraft-X, an autoregressive neural codec language model which unifies multilingual speech editing and zero-shot text-to-speech (TTS) synthesis across 11 languages: English, Mandarin, Korean, Japanese, Spanish, French, German, Dutch, Italian, Portuguese, and Polish. VoiceCraft-X utilizes the Qwen3 large language model for phoneme-free cross-lingual text processing and a novel token reordering mechanism with time-aligned text and speech tokens to handle both tasks as a single sequence generation problem. The model generates high-quality, natural-sounding speech, seamlessly creating new audio or editing existing recordings within one framework. VoiceCraft-X shows robust performance in diverse linguistic settings, even with limited per-language data, underscoring the power of unified autoregressive approaches for advancing complex, real-world multilingual speech applications. Audio samples are available at https://zhishengzheng.com/voicecraft-x/.</abstract>
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%0 Conference Proceedings
%T VoiceCraft-X: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing
%A Zheng, Zhisheng
%A Peng, Puyuan
%A Diwan, Anuj
%A Huynh, Cong Phuoc
%A Sun, Xiaohang
%A Liu, Zhu
%A Bhat, Vimal
%A Harwath, David
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-332-6
%F zheng-etal-2025-voicecraft
%X We introduce VoiceCraft-X, an autoregressive neural codec language model which unifies multilingual speech editing and zero-shot text-to-speech (TTS) synthesis across 11 languages: English, Mandarin, Korean, Japanese, Spanish, French, German, Dutch, Italian, Portuguese, and Polish. VoiceCraft-X utilizes the Qwen3 large language model for phoneme-free cross-lingual text processing and a novel token reordering mechanism with time-aligned text and speech tokens to handle both tasks as a single sequence generation problem. The model generates high-quality, natural-sounding speech, seamlessly creating new audio or editing existing recordings within one framework. VoiceCraft-X shows robust performance in diverse linguistic settings, even with limited per-language data, underscoring the power of unified autoregressive approaches for advancing complex, real-world multilingual speech applications. Audio samples are available at https://zhishengzheng.com/voicecraft-x/.
%U https://aclanthology.org/2025.emnlp-main.137/
%P 2737-2756
Markdown (Informal)
[VoiceCraft-X: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing](https://aclanthology.org/2025.emnlp-main.137/) (Zheng et al., EMNLP 2025)
ACL
- Zhisheng Zheng, Puyuan Peng, Anuj Diwan, Cong Phuoc Huynh, Xiaohang Sun, Zhu Liu, Vimal Bhat, and David Harwath. 2025. VoiceCraft-X: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 2737–2756, Suzhou, China. Association for Computational Linguistics.