4 citations · 11 across the 11 of their papers we have counts for
9 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…
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,…
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…