arXiv Machine Learning

GRAFT: Grafted Reference Audio for Fine-grained Pronunciation in Zero-shot Text-to-Speech

arXiv:2607. 02633v1 Announce Type: new Abstract: We present GRAFT, a per-word pronunciation conditioning mechanism for text-to-speech neural codec language modeling.

Hugging Face Trending Papers

Aug 12

Confucius4-TTS: Transcript-Free Cross-Lingual Zero-Shot TTS with a Learnable Speaker Encoder

Recent advances in zero-shot text-to-speech (TTS) have substantially improved speech quality and voice cloning fidelity. However, many zero-shot TTS systems still depend on audio prompt transcripts at inference time.

llms multimodal benchmarks

arXiv AI

Jun 26

VoiceTTA: Enhancing Zero-Shot Text-to-Speech via Reinforcement Learning-Based Test-Time Adaptation

arXiv:2606. 26534v1 Announce Type: cross Abstract: Recently, zero-shot text-to-speech (TTS) has enabled high-fidelity and expressive speech synthesis, but it often fails to imitate unseen speaking styles from uncommon scenarios (e.

By Tianxin Xie, Chenxing Li, Dong Yu, Li Liu

diffusion reinforcement-learning fine-tuning multimodal benchmarks

arXiv Machine Learning

Jul 20

RobustSpeechFlow: Learning Robust Text-to-Speech Trajectories via Augmentation-based Contrastive Flow Matching

arXiv:2605. 22083v2 Announce Type: replace-cross Abstract: While flow-matching text-to-speech (TTS) achieves strong zero-shot speaker similarity and naturalness, it remains susceptible to content fidelity issues, particularly skip and repeat errors from imperfect alignment.

By Jinhyeok Yang, Hyeongju Kim, Yechan Yu, Joon Byun, Frederik Bous, Juheon Lee

diffusion multimodal benchmarks safety

arXiv AI

Jun 19

FlowEdit: Associative Memory for Lifelong Pronunciation Adaptation in Flow-Matching TTS

arXiv:2606. 20518v1 Announce Type: new Abstract: Flow-matching text-to-speech systems achieve remarkable zero-shot quality but remain static after deployment: pronunciation errors on out-of-vocabulary proper nouns persist unless the model is retrained.

By Harshit Singh, Ayush Pratap Singh, Nityanand Mathur

rag multimodal benchmarks

arXiv Machine Learning

Jun 9

From A to B to A: Palindromic Zero-Shot Voice Conversion with Non-Parallel Data

arXiv:2606. 08843v1 Announce Type: cross Abstract: We present a voice conversion (VC) framework that utilizes K-Nearest Neighbors (KNN) retrieval over WavLM representations to align non-parallel source and target speech, constructing synthetic training pairs for supervised learning.

By Moshe Mandel, Shlomo E. Chazan

safety

arXiv Machine Learning

Jun 19

Low-Burden Data Augmentation for Dysarthric ASR via Zero-Shot Voice Cloning

arXiv:2606. 19823v1 Announce Type: cross Abstract: Automatic speech recognition remains unreliable for dysarthric speech due to data scarcity and high inter-speaker variability.

By Satwinder Singh, Qianli Wang, Zihan Zhong, Clarion Mendes, Hasegawa-Johnson, Waleed Abdulla, Seyed Reza Shahamiri

fine-tuning multimodal

arXiv AI

1d ago

Adding Voice Cloning to Text-to-Audio-Video Models with a Single Zero-Initialised Layer

arXiv:2608. 15690v1 Announce Type: cross Abstract: Text-to-audio-video (T2AV) generation models produce a video and its soundtrack from a textual description, but offer no control over whose voice speaks in the output.

By Ivan Mikheev, Viacheslav Vasilev, Anna Dmitrienko, Alexey Letunovskiy, Ivan Kirillov, Kirill Chernyshev, Denis Dimitrov

rag diffusion fine-tuning multimodal benchmarks

arXiv AI

Jun 9

GenTSE: Enhancing Target Speaker Extraction via a Coarse-to-Fine Generative Language Model

arXiv:2512. 20978v2 Announce Type: replace-cross Abstract: Language Model (LM)-based generative modeling has emerged as a promising direction for TSE, offering potential for improved generalization and high-fidelity speech.

By Haoyang Li, Xuyi Zhuang, Azmat Adnan, Ye Ni, Wei Rao, Shreyas Gopal, Eng Siong Chng, Boon Siew Han, Yuanjin Zheng

llms rag reinforcement-learning safety

arXiv AI

Jul 17

Large Audio Language Models for Spoofing-Aware Speaker Verification

arXiv:2607. 14753v1 Announce Type: cross Abstract: Recent advances in text-to-speech and voice cloning make high-quality spoofing inexpensive and scalable, threatening voice authentication systems, especially automatic speaker verification (ASV).

By Sofya Savelyeva, Mariia Perunova, Evgeny Kushnir, Artem Dvirniak, Dmitrii Korzh, Oleg Y. Rogov

llms multimodal

arXiv AI

Jun 10

Speech Meets ELF: Audio Conditional Continuous-Target Diffusion for Speech Recognition and Translation

arXiv:2606. 10368v1 Announce Type: cross Abstract: Speech-to-text (S2T) systems for recognition (ASR) and translation (S2TT) typically generate discrete text tokens.

By Xuanchen Li, Tianrui Wang, Yuheng Lu, Zikang Huang, Yu Jiang, Chenghan Lin, Chenrui Cui, Ziyang Ma, Xingyu Ma, Chunyu Qiang, Guochen Yu, Xie Chen, Longbiao Wang, Jianwu Dang

diffusion multimodal

arXiv AI

Jun 24

ZONOS2 Technical Report

arXiv:2606. 24320v1 Announce Type: cross Abstract: We present ZONOS2 8B, our latest TTS model, which achieves state-of-the-art naturalness, prosody, and voice cloning fidelity.

By Gabriel Clark, Sofian Mejjoute, Mohamed Osman, George Close, Beren Millidge

efficiency benchmarks

arXiv AI

Jun 19

ZeSTA: Zero-Shot TTS Augmentation with Domain-Conditioned Training for Data-Efficient Personalized Speech Synthesis

arXiv:2603. 04219v2 Announce Type: replace-cross Abstract: We investigate the use of zero-shot text-to-speech (ZS-TTS) as a data augmentation source for low-resource personalized speech synthesis.

By Youngwon Choi, Jinwoo Oh, Hwayeon Kim, Hyeonyu Kim

rag fine-tuning multimodal

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