11 citations · 25 across the 13 of their papers we have counts for
5 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…
Few-shot acoustic event detection via meta-learning
Bowen Shi, Ming Sun, Krishna C. Puvvada +3
We study few-shot acoustic event detection (AED) in this paper. Few-shot learning enables detection of new events with very limited labeled data. Compared to other research areas l…
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…