Noise-Robust Speech Emotion Recognition Using Denoising Autoencoder

Ha HK, Kim NK, Seong WK, Kim HK. Noise-Robust Speech Emotion Recognition Using Denoising Autoencoder. In: AES Convention 140. Audio Engineering Society; 2016. Paper 260. Available from: https://aes.org/publications/elibrary-page/?id=18164

@inproceedings{Ha2016_18164,
  author = {Ha, Hun Kyu and Kim, Nam Kyun and Seong, Woo Kyeong and Kim, Hong Kook},
  title = {{Noise-Robust Speech Emotion Recognition Using Denoising Autoencoder}},
  booktitle = {AES Convention 140},
  note = {Paper 260},
  year = {2016},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18164}
}

TY  - CPAPER
TI  - Noise-Robust Speech Emotion Recognition Using Denoising Autoencoder
AU  - Ha, Hun Kyu
AU  - Kim, Nam Kyun
AU  - Seong, Woo Kyeong
AU  - Kim, Hong Kook
T2  - AES Convention 140
M1  - Paper 260
PY  - 2016
DA  - 2016/05/06
UR  - https://aes.org/publications/elibrary-page/?id=18164
PB  - Audio Engineering Society
LA  - en
AB  - In this paper, a method of noise-robust speech emotion recognition under music noises is proposed by using a denoising autoencoder (DAE) and a support vector machine (SVM). The proposed method first trains a DAE by using emotional speech signals corrupted by music noises. Then, the output values from a middle layer of the DAE are used as speech features. Next, an SVM is trained to classify emotions using the DAE features. The performance of the proposed method is compared with that of a conventional SVM classifier. Consequently, it is shown that the proposed method relatively improves the overall emotion recognition rate by 9.76% under music noise conditions, compared to the conventional method.
ER  -