13 citations · 40 across the 16 of their papers we have counts for
16 papers
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…
PM-MMUT: Boosted Phone-Mask Data Augmentation using Multi-Modeling Unit Training for Phonetic-Reduction-Robust E2E Speech Recognition
Guodong Ma, Pengfei Hu, Nurmemet Yolwas +2
Consonant and vowel reduction are often encountered in speech, which might cause performance degradation in automatic speech recognition (ASR). Our recently proposed learning strat…
Minimum word error training for non-autoregressive Transformer-based code-switching ASR
Yizhou Peng, Jicheng Zhang, Haihua Xu +2
Non-autoregressive end-to-end ASR framework might be potentially appropriate for code-switching recognition task thanks to its inherent property that present output token being ind…
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition
Jicheng Zhang, Yizhou Peng, Pham Van Tung +3
In this paper, we propose a single multi-task learning framework to perform End-to-End (E2E) speech recognition (ASR) and accent recognition (AR) simultaneously. The proposed frame…
Enriching Under-Represented Named-Entities To Improve Speech Recognition Performance
Tingzhi Mao, Yerbolat Khassanov, Van Tung Pham +4
Automatic speech recognition (ASR) for under-represented named-entity (UR-NE) is challenging due to such named-entities (NE) have insufficient instances and poor contextual coverag…
The NTU-AISG Text-to-speech System for Blizzard Challenge 2020
Haobo Zhang, Tingzhi Mao, Haihua Xu +1
We report our NTU-AISG Text-to-speech (TTS) entry systems for the Blizzard Challenge 2020 in this paper. There are two TTS tasks in this year's challenge, one is a Mandarin TTS tas…
Multilingual Approach to Joint Speech and Accent Recognition with DNN-HMM Framework
Yizhou Peng, Jicheng Zhang, Haobo Zhang +3
Human can recognize speech, as well as the peculiar accent of the speech simultaneously. However, present state-of-the-art ASR system can rarely do that. In this paper, we propose…
Monolingual Data Selection Analysis for English-Mandarin Hybrid Code-switching Speech Recognition
Haobo Zhang, Haihua Xu, Van Tung Pham +2
In this paper, we conduct data selection analysis in building an English-Mandarin code-switching (CS) speech recognition (CSSR) system, which is aimed for a real CSSR contest in Ch…
Approaches to Improving Recognition of Underrepresented Named Entities in Hybrid ASR Systems
Tingzhi Mao, Yerbolat Khassanov, Van Tung Pham +3
In this paper, we present a series of complementary approaches to improve the recognition of underrepresented named entities (NE) in hybrid ASR systems without compromising overall…
Mandarin tone modeling using recurrent neural networks
Hao Huang, Ying Hu, Haihua Xu
We propose an Encoder-Classifier framework to model the Mandarin tones using recurrent neural networks (RNN). In this framework, extracted frames of features for tone classificatio…