activity
20162025
most citedTowards More Accurate Automatic Sleep Staging via Deep Transfer Learning

159 citations · 402 across the 20 of their papers we have counts for

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Showing 2020Show all

9 papers · 1 filter

cs.SD2020★ 10 cited

Universal ASR: Unifying Streaming and Non-Streaming ASR Using a Single Encoder-Decoder Model

Zhifu Gao, Shiliang Zhang, Ming Lei +1

Recently, online end-to-end ASR has gained increasing attention. However, the performance of online systems still lags far behind that of offline systems, with a large gap in quali…

cs.HC2020★ 9 cited

Incandescent Bulb and LED Brake Lights:Novel Analysis of Reaction Times

Ramaswamy Palaniappan, Surej Mouli, Evangelina Fringi +2

Rear-end collision accounts for around 8% of all vehicle crashes in the UK, with the failure to notice or react to a brake light signal being a major contributory cause. Meanwhile…

cs.SD2020

Self-Attention Generative Adversarial Network for Speech Enhancement

Huy Phan, Huy Le Nguyen, Oliver Y. Chén +4

Existing generative adversarial networks (GANs) for speech enhancement solely rely on the convolution operation, which may obscure temporal dependencies across the sequence input.…

eess.AS2020★ 16 cited

On Multitask Loss Function for Audio Event Detection and Localization

Huy Phan, Lam Pham, Philipp Koch +3

Audio event localization and detection (SELD) have been commonly tackled using multitask models. Such a model usually consists of a multi-label event classification branch with sig…

cs.SD2020★ 9 cited

SAN-M: Memory Equipped Self-Attention for End-to-End Speech Recognition

Zhifu Gao, Shiliang Zhang, Ming Lei +1

End-to-end speech recognition has become popular in recent years, since it can integrate the acoustic, pronunciation and language models into a single neural network. Among end-to-…

eess.AS2020

Deep Feature Embedding and Hierarchical Classification for Audio Scene Classification

Lam Pham, Ian McLoughlin, Huy Phan +2

In this work, we propose an approach that features deep feature embedding learning and hierarchical classification with triplet loss function for Acoustic Scene Classification (ASC…

cs.SD2020

Robust Acoustic Scene Classification using a Multi-Spectrogram Encoder-Decoder Framework

Lam Pham, Huy Phan, Truc Nguyen +3

This article proposes an encoder-decoder network model for Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording from its acoustic signature.…

cs.SD2020

Robust Deep Learning Framework For Predicting Respiratory Anomalies and Diseases

Lam Pham, Ian McLoughlin, Huy Phan +3

This paper presents a robust deep learning framework developed to detect respiratory diseases from recordings of respiratory sounds. The complete detection process firstly involves…

cs.LG2020★ 133 cited

Improving GANs for Speech Enhancement

Huy Phan, Ian V. McLoughlin, Lam Pham +4

Generative adversarial networks (GAN) have recently been shown to be efficient for speech enhancement. However, most, if not all, existing speech enhancement GANs (SEGAN) make use…