20 citations · 51 across the 21 of their papers we have counts for
6 papers · 1 filter
FD-Bench: A Full-Duplex Benchmarking Pipeline Designed for Full Duplex Spoken Dialogue Systems
Yizhou Peng, Yi-Wen Chao, Dianwen Ng +4
Full-duplex spoken dialogue systems (FDSDS) enable more natural human-machine interactions by allowing real-time user interruptions and backchanneling, compared to traditional SDS…
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions
Kun Zhou, You Zhang, Dianwen Ng +3
Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…
Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis
Kun Zhou, Shengkui Zhao, Yukun Ma +7
Recent language model-based text-to-speech (TTS) frameworks demonstrate scalability and in-context learning capabilities. However, they suffer from robustness issues due to the acc…
SPGM: Prioritizing Local Features for enhanced speech separation performance
Jia Qi Yip, Shengkui Zhao, Yukun Ma +8
Dual-path is a popular architecture for speech separation models (e.g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separatel…
A Unified Speaker Adaptation Approach for ASR
Yingzhu Zhao, Chongjia Ni, Cheung-Chi Leung +3
Transformer models have been used in automatic speech recognition (ASR) successfully and yields state-of-the-art results. However, its performance is still affected by speaker mism…
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning
Zhiping Zeng, Van Tung Pham, Haihua Xu +4
In this work, we study leveraging extra text data to improve low-resource end-to-end ASR under cross-lingual transfer learning setting. To this end, we extend our prior work [1], a…