50 citations · 57 across the 18 of their papers we have counts for
19 papers
FD-Bench: A Full-Duplex Benchmarking Pipeline Designed for Full Duplex Spoken Dialogue Systems
Yizhou Peng, Yi-Wen Chao, Dianwen Ng +4
Full-duplex spoken dialogue systems (FDSDS) enable more natural human-machine interactions by allowing real-time user interruptions and backchanneling, compared to traditional SDS…
Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding
Dianwen Ng, Kun Zhou, Yi-Wen Chao +3
Achieving high-fidelity audio compression while preserving perceptual quality across diverse content remains a key challenge in Neural Audio Coding (NAC). We introduce MUFFIN, a fu…
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions
Kun Zhou, You Zhang, Dianwen Ng +3
Emotional text-to-speech (TTS) systems sturggle to capture the full spectrum of human emotions due to the inherent complexity of emotional expressions and the limited coverage of e…
Towards Audio Codec-based Speech Separation
Jia Qi Yip, Shengkui Zhao, Dianwen Ng +2
Recent improvements in neural audio codec (NAC) models have generated interest in adopting pre-trained codecs for a variety of speech processing applications to take advantage of t…
Phonetic Enhanced Language Modeling for Text-to-Speech Synthesis
Kun Zhou, Shengkui Zhao, Yukun Ma +7
Recent language model-based text-to-speech (TTS) frameworks demonstrate scalability and in-context learning capabilities. However, they suffer from robustness issues due to the acc…
MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation
Shengkui Zhao, Yukun Ma, Chongjia Ni +7
Our previously proposed MossFormer has achieved promising performance in monaural speech separation. However, it predominantly adopts a self-attention-based MossFormer module, whic…
Are Soft Prompts Good Zero-shot Learners for Speech Recognition?
Dianwen Ng, Chong Zhang, Ruixi Zhang +7
Large self-supervised pre-trained speech models require computationally expensive fine-tuning for downstream tasks. Soft prompt tuning offers a simple parameter-efficient alternati…
Analysis of Speech Separation Performance Degradation on Emotional Speech Mixtures
Jia Qi Yip, Dianwen Ng, Bin Ma +1
Despite recent strides made in Speech Separation, most models are trained on datasets with neutral emotions. Emotional speech has been known to degrade performance of models in a v…
SPGM: Prioritizing Local Features for enhanced speech separation performance
Jia Qi Yip, Shengkui Zhao, Yukun Ma +8
Dual-path is a popular architecture for speech separation models (e.g. Sepformer) which splits long sequences into overlapping chunks for its intra- and inter-blocks that separatel…
ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention
Jia Qi Yip, Tuan Truong, Dianwen Ng +7
In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetri…
Contrastive Speech Mixup for Low-resource Keyword Spotting
Dianwen Ng, Ruixi Zhang, Jia Qi Yip +6
Most of the existing neural-based models for keyword spotting (KWS) in smart devices require thousands of training samples to learn a decent audio representation. However, with the…
Adaptive Knowledge Distillation between Text and Speech Pre-trained Models
Jinjie Ni, Yukun Ma, Wen Wang +7
Learning on a massive amount of speech corpus leads to the recent success of many self-supervised speech models. With knowledge distillation, these models may also benefit from the…
deHuBERT: Disentangling Noise in a Self-supervised Model for Robust Speech Recognition
Dianwen Ng, Ruixi Zhang, Jia Qi Yip +7
Existing self-supervised pre-trained speech models have offered an effective way to leverage massive unannotated corpora to build good automatic speech recognition (ASR). However,…
I2CR: Improving Noise Robustness on Keyword Spotting Using Inter-Intra Contrastive Regularization
Dianwen Ng, Jia Qi Yip, Tanmay Surana +6
Noise robustness in keyword spotting remains a challenge as many models fail to overcome the heavy influence of noises, causing the deterioration of the quality of feature embeddin…
Amino Acid Classification in 2D NMR Spectra via Acoustic Signal Embeddings
Jia Qi Yip, Dianwen Ng, Bin Ma +2
Nuclear Magnetic Resonance (NMR) is used in structural biology to experimentally determine the structure of proteins, which is used in many areas of biology and is an important par…
Small Footprint Multi-channel ConvMixer for Keyword Spotting with Centroid Based Awareness
Dianwen Ng, Jin Hui Pang, Yang Xiao +3
It is critical for a keyword spotting model to have a small footprint as it typically runs on-device with low computational resources. However, maintaining the previous SOTA perfor…
ConvMixer: Feature Interactive Convolution with Curriculum Learning for Small Footprint and Noisy Far-field Keyword Spotting
Dianwen Ng, Yunqi Chen, Biao Tian +2
Building efficient architecture in neural speech processing is paramount to success in keyword spotting deployment. However, it is very challenging for lightweight models to achiev…
On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR
Zhao Yang, Dianwen Ng, Xiao Fu +5
End-to-end automatic speech recognition (ASR) has achieved promising results. However, most existing end-to-end ASR methods neglect the use of specific language characteristics. Fo…
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals
Xiang Lan, Dianwen Ng, Shenda Hong +1
Learning information-rich and generalizable representations effectively from unlabeled multivariate cardiac signals to identify abnormal heart rhythms (cardiac arrhythmias) is valu…