Bird Sound Classification Using Convolutional Neural Networks
- Chih-Yuan Koh, Jaw-Yuan Chang, Chiang-Lin Tai, Da Huang, Han-Hsing Hsieh, Yi-Wen Liu
Conference and Labs of the Evaluation Forum
The inception model achieved 0.16 classification mean average precision (c-mAP) and ranked the second place among five teams that successfully submitted their predictions in the BirdCLEF2019 competition.
Filter-based Discriminative Autoencoders for Children Speech Recognition
- Chiang-Lin Tai, Hung-Shin Lee, Yu Tsao, Hsin-Min Wang
- 1 April 2022
A filter-based discriminative autoencoder for acoustic modeling that can make the phonetic embedding purer, resulting in more accurate senone (triphone-state) scores is proposed.