13 citations · 40 across the 16 of their papers we have counts for
7 papers · 1 filter
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…
SRTNet: Time Domain Speech Enhancement Via Stochastic Refinement
Zhibin Qiu, Mengfan Fu, Yinfeng Yu +3
Diffusion model, as a new generative model which is very popular in image generation and audio synthesis, is rarely used in speech enhancement. In this paper, we use the diffusion…
Intermediate-layer output Regularization for Attention-based Speech Recognition with Shared Decoder
Jicheng Zhang, Yizhou Peng, Haihua Xu +3
Intermediate layer output (ILO) regularization by means of multitask training on encoder side has been shown to be an effective approach to yielding improved results on a wide rang…
Internal Language Model Estimation based Language Model Fusion for Cross-Domain Code-Switching Speech Recognition
Yizhou Peng, Yufei Liu, Jicheng Zhang +4
Internal Language Model Estimation (ILME) based language model (LM) fusion has been shown significantly improved recognition results over conventional shallow fusion in both intra-…
A Graph Isomorphism Network with Weighted Multiple Aggregators for Speech Emotion Recognition
Ying Hu, Yuwu Tang, Hao Huang +1
Speech emotion recognition (SER) is an essential part of human-computer interaction. In this paper, we propose an SER network based on a Graph Isomorphism Network with Weighted Mul…
Leveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition
Guodong Ma, Pengfei Hu, Jian Kang +2
In Uyghur speech, consonant and vowel reduction are often encountered, especially in spontaneous speech with high speech rate, which will cause a degradation of speech recognition…
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…