36 citations · 195 across the 52 of their papers we have counts for
52 papers
Codec Data Augmentation for Time-domain Heart Sound Classification
Ansh Mishra, Jia Qi Yip, Eng Siong Chng
Heart auscultations are a low-cost and effective way of detecting valvular heart diseases early, which can save lives. Nevertheless, it has been difficult to scale this screening m…
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…
MIR-GAN: Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognition
Yuchen Hu, Chen Chen, Ruizhe Li +2
Audio-visual speech recognition (AVSR) attracts a surge of research interest recently by leveraging multimodal signals to understand human speech. Mainstream approaches addressing…
A Neural State-Space Model Approach to Efficient Speech Separation
Chen Chen, Chao-Han Huck Yang, Kai Li +3
In this work, we introduce S4M, a new efficient speech separation framework based on neural state-space models (SSM). Motivated by linear time-invariant systems for sequence modeli…
Study of GANs for Noisy Speech Simulation from Clean Speech
Leander Melroy Maben, Zixun Guo, Chen Chen +2
The performance of speech processing models trained on clean speech drops significantly in noisy conditions. Training with noisy datasets alleviates the problem, but procuring such…
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…
UniS-MMC: Multimodal Classification via Unimodality-supervised Multimodal Contrastive Learning
Heqing Zou, Meng Shen, Chen Chen +3
Multimodal learning aims to imitate human beings to acquire complementary information from multiple modalities for various downstream tasks. However, traditional aggregation-based…
Metric-oriented Speech Enhancement using Diffusion Probabilistic Model
Chen Chen, Yuchen Hu, Weiwei Weng +1
Deep neural network based speech enhancement technique focuses on learning a noisy-to-clean transformation supervised by paired training data. However, the task-specific evaluation…
Unsupervised Noise adaptation using Data Simulation
Chen Chen, Yuchen Hu, Heqing Zou +2
Deep neural network based speech enhancement approaches aim to learn a noisy-to-clean transformation using a supervised learning paradigm. However, such a trained-well transformati…
Unifying Speech Enhancement and Separation with Gradient Modulation for End-to-End Noise-Robust Speech Separation
Yuchen Hu, Chen Chen, Heqing Zou +2
Recent studies in neural network-based monaural speech separation (SS) have achieved a remarkable success thanks to increasing ability of long sequence modeling. However, they woul…
Probabilistic Back-ends for Online Speaker Recognition and Clustering
Alexey Sholokhov, Nikita Kuzmin, Kong Aik Lee +1
This paper focuses on multi-enrollment speaker recognition which naturally occurs in the task of online speaker clustering, and studies the properties of different scoring back-end…
Improving Spoken Language Identification with Map-Mix
Shangeth Rajaa, Kriti Anandan, Swaraj Dalmia +2
The pre-trained multi-lingual XLSR model generalizes well for language identification after fine-tuning on unseen languages. However, the performance significantly degrades when th…
Punctuation Restoration for Singaporean Spoken Languages: English, Malay, and Mandarin
Abhinav Rao, Ho Thi-Nga, Chng Eng-Siong
This paper presents the work of restoring punctuation for ASR transcripts generated by multilingual ASR systems. The focus languages are English, Mandarin, and Malay which are thre…
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…
DENT-DDSP: Data-efficient noisy speech generator using differentiable digital signal processors for explicit distortion modelling and noise-robust speech recognition
Z. Guo, C. Chen, E. S. Chng
The performances of automatic speech recognition (ASR) systems degrade drastically under noisy conditions. Explicit distortion modelling (EDM), as a feature compensation step, is a…
Continual Learning For On-Device Environmental Sound Classification
Yang Xiao, Xubo Liu, James King +4
Continuously learning new classes without catastrophic forgetting is a challenging problem for on-device environmental sound classification given the restrictions on computation re…
Language-Based Audio Retrieval with Converging Tied Layers and Contrastive Loss
Andrew Koh, Eng Siong Chng
In this paper, we tackle the new Language-Based Audio Retrieval task proposed in DCASE 2022. Firstly, we introduce a simple, scalable architecture which ties both the audio and tex…
Automated Audio Captioning with Epochal Difficult Captions for Curriculum Learning
Andrew Koh, Soham Tiwari, Chng Eng Siong
In this paper, we propose an algorithm, Epochal Difficult Captions, to supplement the training of any model for the Automated Audio Captioning task. Epochal Difficult Captions is a…
Self-critical Sequence Training for Automatic Speech Recognition
Chen Chen, Yuchen Hu, Nana Hou +3
Although automatic speech recognition (ASR) task has gained remarkable success by sequence-to-sequence models, there are two main mismatches between its training and testing that m…
Interactive Audio-text Representation for Automated Audio Captioning with Contrastive Learning
Chen Chen, Nana Hou, Yuchen Hu +3
Automated Audio captioning (AAC) is a cross-modal task that generates natural language to describe the content of input audio. Most prior works usually extract single-modality acou…
Speech Emotion Recognition with Co-Attention based Multi-level Acoustic Information
Heqing Zou, Yuke Si, Chen Chen +2
Speech Emotion Recognition (SER) aims to help the machine to understand human's subjective emotion from only audio information. However, extracting and utilizing comprehensive in-d…
Noise-robust Speech Recognition with 10 Minutes Unparalleled In-domain Data
Chen Chen, Nana Hou, Yuchen Hu +2
Noise-robust speech recognition systems require large amounts of training data including noisy speech data and corresponding transcripts to achieve state-of-the-art performances in…
Estimation of speaker age and height from speech signal using bi-encoder transformer mixture model
Tarun Gupta, Duc-Tuan Truong, Tran The Anh +1
The estimation of speaker characteristics such as age and height is a challenging task, having numerous applications in voice forensic analysis. In this work, we propose a bi-encod…
Dual-Path Style Learning for End-to-End Noise-Robust Speech Recognition
Yuchen Hu, Nana Hou, Chen Chen +1
Automatic speech recognition (ASR) systems degrade significantly under noisy conditions. Recently, speech enhancement (SE) is introduced as front-end to reduce noise for ASR, but i…