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20122024
most citedCompression of Acoustic Event Detection Models with Low-rank Matrix Factorization and Quantization Training

11 citations · 25 across the 13 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

eess.AS2019

Acoustic scene analysis with multi-head attention networks

Weimin Wang, Weiran Wang, Ming Sun +1

Acoustic Scene Classification (ASC) is a challenging task, as a single scene may involve multiple events that contain complex sound patterns. For example, a cooking scene may conta…

eess.AS20192 cited

Sub-band Convolutional Neural Networks for Small-footprint Spoken Term Classification

Chieh-Chi Kao, Ming Sun, Yixin Gao +2

This paper proposes a Sub-band Convolutional Neural Network for spoken term classification. Convolutional neural networks (CNNs) have proven to be very effective in acoustic applic…

eess.AS2019

Compression of Acoustic Event Detection Models With Quantized Distillation

Bowen Shi, Ming Sun, Chieh-Chi Kao +3

Acoustic Event Detection (AED), aiming at detecting categories of events based on audio signals, has found application in many intelligent systems. Recently deep neural network sig…

eess.AS201911 cited

Compression of Acoustic Event Detection Models with Low-rank Matrix Factorization and Quantization Training

Bowen Shi, Ming Sun, Chieh-Chi Kao +3

In this paper, we present a compression approach based on the combination of low-rank matrix factorization and quantization training, to reduce complexity for neural network based…

eess.AS2019

Semi-supervised Acoustic Event Detection based on tri-training

Bowen Shi, Ming Sun, Chieh-Chi Kao +3

This paper presents our work of training acoustic event detection (AED) models using unlabeled dataset. Recent acoustic event detectors are based on large-scale neural networks, wh…