8 citations · 28 across the 50 of their papers we have counts for
29 papers · 1 filter
Spontaneous Style Text-to-Speech Synthesis with Controllable Spontaneous Behaviors Based on Language Models
Weiqin Li, Peiji Yang, Yicheng Zhong +5
Spontaneous style speech synthesis, which aims to generate human-like speech, often encounters challenges due to the scarcity of high-quality data and limitations in model capabili…
Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation
Mengzhe Geng, Xurong Xie, Jiajun Deng +7
The application of data-intensive automatic speech recognition (ASR) technologies to dysarthric and elderly adult speech is confronted by their mismatch against healthy and nonaged…
CoLM-DSR: Leveraging Neural Codec Language Modeling for Multi-Modal Dysarthric Speech Reconstruction
Xueyuan Chen, Dongchao Yang, Dingdong Wang +3
Dysarthric speech reconstruction (DSR) aims to transform dysarthric speech into normal speech. It still suffers from low speaker similarity and poor prosody naturalness. In this pa…
Joint Speaker Features Learning for Audio-visual Multichannel Speech Separation and Recognition
Guinan Li, Jiajun Deng, Youjun Chen +8
This paper proposes joint speaker feature learning methods for zero-shot adaptation of audio-visual multichannel speech separation and recognition systems. xVector and ECAPA-TDNN s…
UniAudio 1.5: Large Language Model-driven Audio Codec is A Few-shot Audio Task Learner
Dongchao Yang, Haohan Guo, Yuanyuan Wang +5
The Large Language models (LLMs) have demonstrated supreme capabilities in text understanding and generation, but cannot be directly applied to cross-modal tasks without fine-tunin…
SimpleSpeech: Towards Simple and Efficient Text-to-Speech with Scalar Latent Transformer Diffusion Models
Dongchao Yang, Dingdong Wang, Haohan Guo +3
In this study, we propose a simple and efficient Non-Autoregressive (NAR) text-to-speech (TTS) system based on diffusion, named SimpleSpeech. Its simpleness shows in three aspects:…