師 資 介 紹
人工智慧與機器人碩士學程 > 師資介紹-洪志偉
教授
洪志偉
學歷
國立臺灣大學電機工程學系研究所博士
研究領域
數位信號處理、數位語音處理、語音處理應用
研究室
科一415
- jwhung@ncnu.edu.tw
- (049)2910960 #4802
- 個人網站
研究成果
期刊論文
- Yu, K-H. Hung, S-S. Wang, Y. Tsao and J-W. Hung, “Time-domain multi-modal bone/air conducted speech enhancement,” IEEE Signal Processing Letters, 2020.
- S-S. Wang, P. Lin, Y. Tsao, J-W. Hung, B. Su, “Suppression by selecting wavelets for feature compression in distributed speech recognition,” IEEE/ACM Trans. on Audio, Speech, and Language Processing, March 2018 (SCI)
- J-W. Hung, J-S. Lin and P-J. Wu, “Employing robust principal component analysis for noise-robust speech feature extraction in automatic speech recognition with the structure of a deep neural network,” Applied System Innovation, Aug 2018
- S-K. Lee, J-W. Hung, “An evaluation study of using various SNR-level training data in the denoising autoencoder (DAE) technique for speech enhancement,” International Journal of Electrical, Electronics and Data Communication, Apr 2018
- S-S. Wang, A. Chern, Y. Tsao, J-W. Hung, X. Lu, Y-H. Lai and B. Su, “Wavelet speech enhancement based on nonnegative matrix factorization,” IEEE Signal Processing Letters, May 2016 (SCI)
- J-W. Hung, H-J. Hsieh and B. Chen, “Robust speech recognition via enhancing the complex-valued acoustic spectrum in modulation Domain,” IEEE/ACM Trans. on Audio, Speech, and Language Processing, Feb 2016 (SCI)
- Y-D. Wang, J-H. Jheng, H-J. Hsieh and J-W. Hung, “An evaluation study of speaker and noise adaptation for nonnegative matrix factorization based speech enhancement,” International Journal of Electrical, Electronics and Data Communication, Nov 2015
- H-J. Hsieh, H-T. Fan and J-W. Hung, “Leveraging jointly spatial, temporal and modulation enhancement in creating noise-robust features for speech recognition,” International Journal of Electrical, Electronics and Data Communication, Nov 2015
國際會議論文
- Y-J. Lu, C-F. Liao, X. Lu, J-W. Hung, Y. Tsao, “Incorporating Broad Phonetic Information for Speech Enhancement”, Interspeech 2020
- C-L. Lin, Z-Q. Lin, S-S. Wang, Y. Tsao and J-W. Hung, “Exponentiated magnitude spectrogram-based relative-to-maximum masking for speech enhancement in adverse environments,” IEEE International Conference on Consumer Electronics –Taiwan, 2020
- Z-Q. Lin, C-L. Lin and J-W. Hung, “Lowpass-filtered relative-to-maximum masking for speech enhancement in noise-corrupted environments,” IEEE International Conference on Consumer Electronics –Taiwan, 2020
- S-K. Lee, S-S. Wang, Y. Tsao, J-W. Hung, “Speech enhancement based on reducing the detail portion of speech spectrograms in modulation domain via discrete wavelet transform,” in Proc. ISCSLP, 2018
- J-W. Hung, J-S. Lin and P-J. Wu, “Employing robust principal component analysis for noise-robust speech feature extraction in automatic speech recognition with the structure of deep neural network,” in Proc. ICASI, 2018
- J-W. Hung, J-S. Lin, L-M Lee, S-Yu Wang, “A study of integrating noise-robustness feature extraction techniques with the reduced frame-rate acoustic models in mobile-device speech recognition,” in Proc. AROB, 2018
- C-L. Wu, H-P. Hsu, S-S. Wang, J-W. Hung, Y-H. Lai, H-M. Wang, Y. Tsao, “Wavelet speech enhancement based on robust principal component analysis,” in Proc. Interspeech, 2017
- J-W. Hung and J-S. Lin, “Enhancing the acoustic spectrogram in modulation domain via sparse nonnegative matrix factorization for speech enhancement,” in Proc. AROB, 2017
- C. Yang, S-S. Wang, Y. Tsao and J-W. Hung, “Speech enhancement via ensemble modeling NMF adaptation,” in Proc. ICCE-TW, 2016
- H-J. Hsieh, J-H. Jheng, J-S. Lin and J-W. Hung, “Linear prediction filtering on cepstral time series for noise-robust speech recognition,” in Proc. ICCE-TW, 2016
- S-S. Wang, J. C. Yang; Y. Tsao and J-W. Hung, “Leveraging nonnegative matrix factorization in processing the temporal modulation spectrum for speech enhancement,” in Proc. ICCE-TW, 2016
- J-W. Hung and J-S. Lin, “A study of the noise-robustness algorithms on various types of cepstral feature representation for real-world speech recognition,” in Proc. AROB, 2016