ELEC-E5510 - Speech Recognition D, Lecture, 26.10.2022-9.12.2022
This course space end date is set to 09.12.2022 Search Courses: ELEC-E5510
Reading materials
Completion requirements
Collection of reading materials by topic.
2. Material on project topics
2.9. Deep denoising autoencoder for speech enhancement
- Lu, X., Tsao, Y., Matsuda, S., & Hori, C. (2013). Speech enhancement based on deep denoising autoencoder. In Interspeech (Vol. 2013, pp. 436-440).
- Araki, S., Hayashi, T., Delcroix, M., Fujimoto, M., Takeda, K., & Nakatani, T. (2015). Exploring multi-channel features for denoising-autoencoder-based speech enhancement. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 116-120). IEEE. (if you decide to use multichannel data)
- Gao, T., Du, J., Dai, L. R., & Lee, C. H. (2015). Joint training of front-end and back-end deep neural networks for robust speech recognition. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4375-4379). IEEE.
- Tensorflow implementation