| Speech enhancement based on deep denoising autoencoder. X Lu, Y Tsao, S Matsuda, C Hori Interspeech 2013, 436-440, 2013 | 1099 | 2013 |
| End-to-end waveform utterance enhancement for direct evaluation metrics optimization by fully convolutional neural networks SW Fu, TW Wang, Y Tsao, X Lu, H Kawai IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (9), 1570 …, 2018 | 343 | 2018 |
| Raw waveform-based speech enhancement by fully convolutional networks SW Fu, Y Tsao, X Lu, H Kawai 2017 Asia-Pacific Signal and Information Processing Association Annual …, 2017 | 272 | 2017 |
| Metricgan+: An improved version of metricgan for speech enhancement SW Fu, C Yu, TA Hsieh, P Plantinga, M Ravanelli, X Lu, Y Tsao arXiv preprint arXiv:2104.03538, 2021 | 227 | 2021 |
| SNR-Aware Convolutional Neural Network Modeling for Speech Enhancement. SW Fu, Y Tsao, X Lu Interspeech, 3768-3772, 2016 | 216 | 2016 |
| Complex spectrogram enhancement by convolutional neural network with multi-metrics learning SW Fu, T Hu, Y Tsao, X Lu 2017 IEEE 27th international workshop on machine learning for signal …, 2017 | 204 | 2017 |
| An investigation of dependencies between frequency components and speaker characteristics for text-independent speaker identification X Lu, J Dang Speech communication 50 (4), 312-322, 2008 | 169 | 2008 |
| A deep denoising autoencoder approach to improving the intelligibility of vocoded speech in cochlear implant simulation YH Lai, F Chen, SS Wang, X Lu, Y Tsao, CH Lee IEEE Transactions on Biomedical Engineering 64 (7), 1568-1578, 2016 | 131 | 2016 |
| Deep learning–based noise reduction approach to improve speech intelligibility for cochlear implant recipients YH Lai, Y Tsao, X Lu, F Chen, YT Su, KC Chen, YH Chen, LC Chen, ... Ear and hearing 39 (4), 795-809, 2018 | 95 | 2018 |
| Speaker adaptive training using deep neural networks T Ochiai, S Matsuda, X Lu, C Hori, S Katagiri 2014 IEEE international conference on acoustics, speech and signal …, 2014 | 82 | 2014 |
| Improving perceptual quality by phone-fortified perceptual loss using wasserstein distance for speech enhancement TA Hsieh, C Yu, SW Fu, X Lu, Y Tsao arXiv preprint arXiv:2010.15174, 2020 | 78 | 2020 |
| Wavecrn: An efficient convolutional recurrent neural network for end-to-end speech enhancement TA Hsieh, HM Wang, X Lu, Y Tsao IEEE Signal Processing Letters 27, 2149-2153, 2020 | 77 | 2020 |
| Ensemble modeling of denoising autoencoder for speech spectrum restoration. X Lu, Y Tsao, S Matsuda, C Hori Interspeech 14, 885-889, 2014 | 77 | 2014 |
| Improving Transformer-Based Speech Recognition Systems with Compressed Structure and Speech Attributes Augmentation. S Li, R Dabre, X Lu, P Shen, T Kawahara, H Kawai Interspeech, 4400-4404, 2019 | 59 | 2019 |
| Maximum a posteriori Based Decoding for CTC Acoustic Models. N Kanda, X Lu, H Kawai Interspeech, 1868-1872, 2016 | 57 | 2016 |
| Speech enhancement using segmental nonnegative matrix factorization HT Fan, J Hung, X Lu, SS Wang, Y Tsao 2014 IEEE international conference on acoustics, speech and signal …, 2014 | 54 | 2014 |
| Sparse representation based on a bag of spectral exemplars for acoustic event detection X Lu, Y Tsao, S Matsuda, C Hori 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 51 | 2014 |
| Speech enhancement based on denoising autoencoder with multi-branched encoders C Yu, RE Zezario, SS Wang, J Sherman, YY Hsieh, X Lu, HM Wang, ... IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 2756-2769, 2020 | 47 | 2020 |
| A model-based investigation of activations of the tongue muscles in vowel production Q Fang, S Fujita, X Lu, J Dang Acoustical Science and Technology 30 (4), 277-287, 2009 | 47 | 2009 |
| Speech restoration based on deep learning autoencoder with layer-wised pretraining. X Lu, S Matsuda, C Hori, H Kashioka Interspeech 2012, 1504-1507, 2012 | 44 | 2012 |