4 citations · 4 across the 14 of their papers we have counts for
11 papers · 1 filter
ProLombard: Structured Multi-Scale Modeling for Normal-to-Lombard Speech Conversion
Hongyang Chen, Xinmeng Xu, Youqiang Zheng +5
Normal-to-Lombard (N2L) speech conversion aims to improve speech intelligibility in noisy environments by transforming normal speech into Lombard-style speech while preserving ling…
Improving Speech Enhancement by Cross- and Sub-band Processing with State Space Model
Jizhen Li, Weiping Tu, Yuhong Yang +3
Recently, the state space model (SSM) represented by Mamba has shown remarkable performance in long-term sequence modeling tasks, including speech enhancement. However, due to subs…
FreeCodec: A disentangled neural speech codec with fewer tokens
Youqiang Zheng, Weiping Tu, Yueteng Kang +5
Neural speech codecs have gained great attention for their outstanding reconstruction with discrete token representations. It is a crucial component in generative tasks such as spe…
SuperCodec: A Neural Speech Codec with Selective Back-Projection Network
Youqiang Zheng, Weiping Tu, Li Xiao +1
Neural speech coding is a rapidly developing topic, where state-of-the-art approaches now exhibit superior compression performance than conventional methods. Despite significant pr…
Improving Speech Enhancement by Integrating Inter-Channel and Band Features with Dual-branch Conformer
Jizhen Li, Xinmeng Xu, Weiping Tu +2
Recent speech enhancement methods based on convolutional neural networks (CNNs) and transformer have been demonstrated to efficaciously capture time-frequency (T-F) information on…
SimuSOE: A Simulated Snoring Dataset for Obstructive Sleep Apnea-Hypopnea Syndrome Evaluation during Wakefulness
Jie Lin, Xiuping Yang, Li Xiao +5
Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a prevalent chronic breathing disorder caused by upper airway obstruction. Previous studies advanced OSAHS evaluation through m…