TY - GEN
T1 - Real-Time Thai Speech Emotion Recognition With Speech Enhancement Using Time-Domain Contrastive Predictive Coding and Conv-Tasnet
AU - Yuenyong, Sumeth
AU - Hnoohom, Narit
AU - Wongpatikaseree, Konlakorn
AU - Singkul, Sattaya
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Speech emotion recognition (SER) is an important part of human-computer interaction. SER face many challenges such as acoustic environment of speech, and the amount of data available for training. For Thai in particular, there is additional challenge from the language using tones, and the size of available dataset is relatively small. In this work we propose Thai Speech Emotion Recognition With Speech Enhancement (TH-SERSE). TH-SERSE consists of speech enhancement using Conv-TasNet followed by pre-training using contrastive predictive coding. The pre-trained model was then finetuned for emotion classification. We experimented on two datasets: EMOLA and ThaiSER that has open and closed acoustic environments, respectively. The experiments show that our method outperforms recently proposed methods.
AB - Speech emotion recognition (SER) is an important part of human-computer interaction. SER face many challenges such as acoustic environment of speech, and the amount of data available for training. For Thai in particular, there is additional challenge from the language using tones, and the size of available dataset is relatively small. In this work we propose Thai Speech Emotion Recognition With Speech Enhancement (TH-SERSE). TH-SERSE consists of speech enhancement using Conv-TasNet followed by pre-training using contrastive predictive coding. The pre-trained model was then finetuned for emotion classification. We experimented on two datasets: EMOLA and ThaiSER that has open and closed acoustic environments, respectively. The experiments show that our method outperforms recently proposed methods.
KW - Thai
KW - contrastive predictive coding
KW - fully-convolutional timedomain audio separation network
KW - speech emotion recognition
KW - speech enhancement
UR - https://www.scopus.com/pages/publications/85133135176
U2 - 10.1109/ICBIR54589.2022.9786444
DO - 10.1109/ICBIR54589.2022.9786444
M3 - Conference contribution
AN - SCOPUS:85133135176
T3 - ICBIR 2022 - 2022 7th International Conference on Business and Industrial Research, Proceedings
SP - 78
EP - 83
BT - ICBIR 2022 - 2022 7th International Conference on Business and Industrial Research, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Business and Industrial Research, ICBIR 2022
Y2 - 19 May 2022 through 20 May 2022
ER -