arXiv AI

AphaVoice: Text-to-Speech Model for Aphasia Patient Simulation

arXiv Machine Learning
Aug 17

VoiceDesigner: Text-to-Voice Generation and Editing via Unified Diffusion Modeling and Data Augmentation

arXiv:2608. 13613v1 Announce Type: cross Abstract: Recent breakthroughs in generative models have made text-to-voice generation (TTV) possible, enabling the synthesis of speech directly from textual voice descriptions.

By Jiarui Hai, Karan Thakkar, Ke Chen, Yunyun Wang, Jiaqi Su, Rithesh Kumar, Mounya Elhilali, Zeyu Jin
Hugging Face Trending Papers
Jul 20

Re-Sonance: A Dysarthric Asynchronous Real-Time Speech Conversion System Based on a Three-Stage Cascaded ASR-LLM-TTS Architecture

Individuals with dysarthria face significant challenges in professional speaking scenarios such as conferences, presentations, and meetings, where real-time communication is crucial. While existing Augmentative and Alternative Communication (AAC) systems provide basic support, they often fail to meet the demands of professional speaking environments due to high latency and unnatural speech patterns.

arXiv Computation and Language
Sep 15

Controllable Dysarthric Speech Synthesis with Patient-Specific Conditioning for Speaker-Diverse ASR Augmentation

arXiv:2602.08696v3 Announce Type: replace-cross Abstract: Dysarthric speech recognition is limited by high speaker variability and scarce labeled data. Existing synthesis methods often couple speaker...

By Haoshen Wang, Xueli Zhong, Bingbing Lin, Jia Huang, Xingduo Pan, Shengxiang Liang, Nizhuan Wang, Wai Ting Siok
arXiv Computation and Language
Oct 12

OpenPA: Forced-alignment-free Multi-granular Pronunciation Assessment with Mixed-transcript Adaptation

OpenPA is a new automatic pronunciation assessment framework that eliminates the need for forced alignment by using Whisper’s cross‑attention to predict word‑ and utterance‑level scores. It adapts to mixed transcripts through mixed‑transcript adaptation and adaptive substitution weighting, enabling a single model to handle both closed‑ and open‑response settings. Trained only on speechocean762, OpenPA outperforms other systems on in‑domain closed and simulated open‑response tests, retains strong zero‑shot performance on MultiPA, and shows promise in oral‑cancer speech evaluation.

By Fu-An Chao, Bi-Cheng Yan, Berlin Chen