24 citations · 107 across the 39 of their papers we have counts for
11 papers · 1 filter
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…
Unsupervised Spoken Term Discovery Based on Re-clustering of Hypothesized Speech Segments with Siamese and Triplet Networks
Man-Ling Sung, Tan Lee
Spoken term discovery from untranscribed speech audio could be achieved via a two-stage process. In the first stage, the unlabelled speech is decoded into a sequence of subword uni…
Fine-grained Style Modeling, Transfer and Prediction in Text-to-Speech Synthesis via Phone-Level Content-Style Disentanglement
Daxin Tan, Tan Lee
This paper presents a novel design of neural network system for fine-grained style modeling, transfer and prediction in expressive text-to-speech (TTS) synthesis. Fine-grained mode…
Text-Independent Speaker Verification with Dual Attention Network
Jingyu Li, Tan Lee
This paper presents a novel design of attention model for text-independent speaker verification. The model takes a pair of input utterances and generates an utterance-level embeddi…
Advancing Multiple Instance Learning with Attention Modeling for Categorical Speech Emotion Recognition
Shuiyang Mao, P. C. Ching, C. -C. Jay Kuo +1
Categorical speech emotion recognition is typically performed as a sequence-to-label problem, i.e., to determine the discrete emotion label of the input utterance as a whole. One o…
EigenEmo: Spectral Utterance Representation Using Dynamic Mode Decomposition for Speech Emotion Classification
Shuiyang Mao, P. C. Ching, Tan Lee
Human emotional speech is, by its very nature, a variant signal. This results in dynamics intrinsic to automatic emotion classification based on speech. In this work, we explore a…
Emotion Profile Refinery for Speech Emotion Classification
Shuiyang Mao, P. C. Ching, Tan Lee
Human emotions are inherently ambiguous and impure. When designing systems to anticipate human emotions based on speech, the lack of emotional purity must be considered. However, m…
Automatic Detection of Phonological Errors in Child Speech Using Siamese Recurrent Autoencoder
Si-Ioi Ng, Tan Lee
Speech sound disorder (SSD) refers to the developmental disorder in which children encounter persistent difficulties in correctly pronouncing words. Assessment of SSD has been rely…
CUCHILD: A Large-Scale Cantonese Corpus of Child Speech for Phonology and Articulation Assessment
Si-Ioi Ng, Cymie Wing-Yee Ng, Jiarui Wang +3
This paper describes the design and development of CUCHILD, a large-scale Cantonese corpus of child speech. The corpus contains spoken words collected from 1,986 child speakers age…