24 citations · 107 across the 39 of their papers we have counts for
39 papers
Measuring Audio's Impact on Correctness: Audio-Contribution-Aware Post-Training of Large Audio Language Models
Haolin He, Xingjian Du, Renhe Sun +16
Large Audio Language Models (LALMs) represent an important frontier in multimodal AI, addressing diverse audio tasks. Recently, post-training of LALMs has received increasing atten…
Low-Resource NMT: A Case Study on the Written and Spoken Languages in Hong Kong
Hei Yi Mak, Tan Lee
The majority of inhabitants in Hong Kong are able to read and write in standard Chinese but use Cantonese as the primary spoken language in daily life. Spoken Cantonese can be tran…
ToneUnit: A Speech Discretization Approach for Tonal Language Speech Synthesis
Dehua Tao, Daxin Tan, Yu Ting Yeung +2
Representing speech as discretized units has numerous benefits in supporting downstream spoken language processing tasks. However, the approach has been less explored in speech syn…
Multivariate Empirical Mode Decomposition of EEG for Mental State Detection at Localized Brain Lobes
Monira Islam, Tan Lee
In this study, the Multivariate Empirical Mode Decomposition (MEMD) approach is applied to extract features from multi-channel EEG signals for mental state classification. MEMD is…
MEMD-HHT based Emotion Detection from EEG using 3D CNN
Monira Islam, Tan Lee
In this study, the Multivariate Empirical Mode Decomposition (MEMD) is applied to multichannel EEG to obtain scale-aligned intrinsic mode functions (IMFs) as input features for emo…
iEmoTTS: Toward Robust Cross-Speaker Emotion Transfer and Control for Speech Synthesis based on Disentanglement between Prosody and Timbre
Guangyan Zhang, Ying Qin, Wenjie Zhang +5
The capability of generating speech with specific type of emotion is desired for many applications of human-computer interaction. Cross-speaker emotion transfer is a common approac…
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech
Wei Liu, Jingyu Li, Tan Lee
The performance of child speech recognition is generally less satisfactory compared to adult speech due to limited amount of training data. Significant performance degradation is e…
CorrectSpeech: A Fully Automated System for Speech Correction and Accent Reduction
Daxin Tan, Liqun Deng, Nianzu Zheng +4
This study propose a fully automated system for speech correction and accent reduction. Consider the application scenario that a recorded speech audio contains certain errors, e.g.…
Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech
Guangyan Zhang, Kaitao Song, Xu Tan +8
Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-b…
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…
Bayesian Learning for Deep Neural Network Adaptation
Xurong Xie, Xunying Liu, Tan Lee +1
A key task for speech recognition systems is to reduce the mismatch between training and evaluation data that is often attributable to speaker differences. Speaker adaptation techn…
The CUHK-TUDELFT System for The SLT 2021 Children Speech Recognition Challenge
Si-Ioi Ng, Wei Liu, Zhiyuan Peng +4
This technical report describes our submission to the 2021 SLT Children Speech Recognition Challenge (CSRC) Track 1. Our approach combines the use of a joint CTC-attention end-to-e…
Unsupervised Pattern Discovery from Thematic Speech Archives Based on Multilingual Bottleneck Features
Man-Ling Sung, Siyuan Feng, Tan Lee
The present study tackles the problem of automatically discovering spoken keywords from untranscribed audio archives without requiring word-by-word speech transcription by automati…