activity
20172022
most citedLeveraging Phone Mask Training for Phonetic-Reduction-Robust E2E Uyghur Speech Recognition

9 citations · 19 across the 8 of their papers we have counts for

collaborators

7 papers

eess.AS20213 cited

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…

eess.AS20212 cited

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…

cs.SD2020

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…

eess.AS2020

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…

eess.AS20201 cited

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…

eess.AS2020

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…