1 citations · 1 across the 6 of their papers we have counts for
6 papers
TFGA-Net: Temporal-Frequency Graph Attention Network for Brain-Controlled Speaker Extraction
Youhao Si, Yuan Liao, Qiushi Han +3
The rapid development of auditory attention decoding (AAD) based on electroencephalography (EEG) signals offers the possibility EEG-driven target speaker extraction. However, how t…
Frequency-Based Alignment of EEG and Audio Signals Using Contrastive Learning and SincNet for Auditory Attention Detection
Yuan Liao, Yuhong Zhang, Qiushi Han +5
Humans exhibit a remarkable ability to focus auditory attention in complex acoustic environments, such as cocktail parties. Auditory attention detection (AAD) aims to identify the…
Bridging Speech and Text: Enhancing ASR with Pinyin-to-Character Pre-training in LLMs
Yang Yuhang, Peng Yizhou, Eng Siong Chng +1
The integration of large language models (LLMs) with pre-trained speech models has opened up new avenues in automatic speech recognition (ASR). While LLMs excel in multimodal under…
Adapting OpenAI's Whisper for Speech Recognition on Code-Switch Mandarin-English SEAME and ASRU2019 Datasets
Yuhang Yang, Yizhou Peng, Xionghu Zhong +2
This paper details the experimental results of adapting the OpenAI's Whisper model for Code-Switch Mandarin-English Speech Recognition (ASR) on the SEAME and ASRU2019 corpora. We c…
Speech-text based multi-modal training with bidirectional attention for improved speech recognition
Yuhang Yang, Haihua Xu, Hao Huang +2
To let the state-of-the-art end-to-end ASR model enjoy data efficiency, as well as much more unpaired text data by multi-modal training, one needs to address two problems: 1) the s…
Hierarchical Softmax for End-to-End Low-resource Multilingual Speech Recognition
Qianying Liu, Zhuo Gong, Zhengdong Yang +8
Low-resource speech recognition has been long-suffering from insufficient training data. In this paper, we propose an approach that leverages neighboring languages to improve low-r…