7 citations · 24 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
Data Techniques For Online End-to-end Speech Recognition
Yang Chen, Weiran Wang, I-Fan Chen +1
Practitioners often need to build ASR systems for new use cases in a short amount of time, given limited in-domain data. While recently developed end-to-end methods largely simplif…
Semi-supervised ASR by End-to-end Self-training
Yang Chen, Weiran Wang, Chao Wang
While deep learning based end-to-end automatic speech recognition (ASR) systems have greatly simplified modeling pipelines, they suffer from the data sparsity issue. In this work,…