11 citations · 25 across the 12 of their papers we have counts for
9 papers · 1 filter
On Front-end Gain Invariant Modeling for Wake Word Spotting
Yixin Gao, Noah D. Stein, Chieh-Chi Kao +4
Wake word (WW) spotting is challenging in far-field due to the complexities and variations in acoustic conditions and the environmental interference in signal transmission. A suite…
Intra-Utterance Similarity Preserving Knowledge Distillation for Audio Tagging
Chun-Chieh Chang, Chieh-Chi Kao, Ming Sun +1
Knowledge Distillation (KD) is a popular area of research for reducing the size of large models while still maintaining good performance. The outputs of larger teacher models are u…
A Joint Framework for Audio Tagging and Weakly Supervised Acoustic Event Detection Using DenseNet with Global Average Pooling
Chieh-Chi Kao, Bowen Shi, Ming Sun +1
This paper proposes a network architecture mainly designed for audio tagging, which can also be used for weakly supervised acoustic event detection (AED). The proposed network cons…
A Comparison of Pooling Methods on LSTM Models for Rare Acoustic Event Classification
Chieh-Chi Kao, Ming Sun, Weiran Wang +1
Acoustic event classification (AEC) and acoustic event detection (AED) refer to the task of detecting whether specific target events occur in audios. As long short-term memory (LST…
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…
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…