24 citations · 107 across the 39 of their papers we have counts for
12 papers · 1 filter
Acoustical Analysis of Speech Under Physical Stress in Relation to Physical Activities and Physical Literacy
Si-Ioi Ng, Rui-Si Ma, Tan Lee +1
Human speech production encompasses physiological processes that naturally react to physic stress. Stress caused by physical activity (PA), e.g., running, may lead to significant c…
Data Augmentation with Locally-time Reversed Speech for Automatic Speech Recognition
Si-Ioi Ng, Tan Lee
Psychoacoustic studies have shown that locally-time reversed (LTR) speech, i.e., signal samples time-reversed within a short segment, can be accurately recognised by human listener…
A study on the efficacy of model pre-training in developing neural text-to-speech system
Guangyan Zhang, Yichong Leng, Daxin Tan +5
In the development of neural text-to-speech systems, model pre-training with a large amount of non-target speakers' data is a common approach. However, in terms of ultimately achie…
Environment Aware Text-to-Speech Synthesis
Daxin Tan, Guangyan Zhang, Tan Lee
This study aims at designing an environment-aware text-to-speech (TTS) system that can generate speech to suit specific acoustic environments. It is also motivated by the desire to…
Improving Text-Independent Speaker Verification with Auxiliary Speakers Using Graph
Jingyu Li, Si-Ioi Ng, Tan Lee
The paper presents a novel approach to refining similarity scores between input utterances for robust speaker verification. Given the embeddings from a pair of input utterances, a…
Utterance-level neural confidence measure for end-to-end children speech recognition
Wei Liu, Tan Lee
Confidence measure is a performance index of particular importance for automatic speech recognition (ASR) systems deployed in real-world scenarios. In the present study, utterance-…
Robust Feature Learning on Long-Duration Sounds for Acoustic Scene Classification
Yuzhong Wu, Tan Lee
Acoustic scene classification (ASC) aims to identify the type of scene (environment) in which a given audio signal is recorded. The log-mel feature and convolutional neural network…
Applying the Information Bottleneck Principle to Prosodic Representation Learning
Guangyan Zhang, Ying Qin, Daxin Tan +1
This paper describes a novel design of a neural network-based speech generation model for learning prosodic representation.The problem of representation learning is formulated acco…
EditSpeech: A Text Based Speech Editing System Using Partial Inference and Bidirectional Fusion
Daxin Tan, Liqun Deng, Yu Ting Yeung +3
This paper presents the design, implementation and evaluation of a speech editing system, named EditSpeech, which allows a user to perform deletion, insertion and replacement of wo…
Detection of Consonant Errors in Disordered Speech Based on Consonant-vowel Segment Embedding
Si-Ioi Ng, Cymie Wing-Yee Ng, Jingyu Li +1
Speech sound disorder (SSD) refers to a type of developmental disorder in young children who encounter persistent difficulties in producing certain speech sounds at the expected ag…
Enhancing Segment-Based Speech Emotion Recognition by Deep Self-Learning
Shuiyang Mao, P. C. Ching, Tan Lee
Despite the widespread utilization of deep neural networks (DNNs) for speech emotion recognition (SER), they are severely restricted due to the paucity of labeled data for training…
CUHK-EE Voice Cloning System for ICASSP 2021 M2VoC Challenge
Daxin Tan, Hingpang Huang, Guangyan Zhang +1
This paper presents the CUHK-EE voice cloning system for ICASSP 2021 M2VoC challenge. The challenge provides two Mandarin speech corpora: the AIShell-3 corpus of 218 speakers with…