11 citations · 17 across the 6 of their papers we have counts for
7 papers
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…
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…
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…
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…
Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting
Ming Sun, Anirudh Raju, George Tucker +6
We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requi…
An Empirical Evaluation of Zero Resource Acoustic Unit Discovery
Chunxi Liu, Jinyi Yang, Ming Sun +7
Acoustic unit discovery (AUD) is a process of automatically identifying a categorical acoustic unit inventory from speech and producing corresponding acoustic unit tokenizations. A…