| iMetricGAN: Intelligibility enhancement for speech-in-noise using generative adversarial network-based metric learning H Li, SW Fu, Y Tsao, J Yamagishi arXiv preprint arXiv:2004.00932, 2020 | 21 | 2020 |
| Improved prosody from learned f0 codebook representations for vq-vae speech waveform reconstruction Y Zhao, H Li, CI Lai, J Williams, E Cooper, J Yamagishi arXiv preprint arXiv:2005.07884, 2020 | 19 | 2020 |
| Noise tokens: Learning neural noise templates for environment-aware speech enhancement H Li, J Yamagishi arXiv preprint arXiv:2004.04001, 2020 | 19 | 2020 |
| Multi-Metric Optimization Using Generative Adversarial Networks for Near-End Speech Intelligibility Enhancement H Li, J Yamagishi IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 3000-3011, 2021 | 10 | 2021 |
| Denoising-and-Dereverberation Hierarchical Neural Vocoder for Robust Waveform Generation Y Ai, H Li, X Wang, J Yamagishi, Z Ling 2021 IEEE Spoken Language Technology Workshop (SLT), 477-484, 2021 | 5 | 2021 |
| DDS: A new device-degraded speech dataset for speech enhancement H Li, J Yamagishi arXiv preprint arXiv:2109.07931, 2021 | 3 | 2021 |
| Enhancing Low-Quality Voice Recordings Using Disentangled Channel Factor and Neural Waveform Model H Li, Y Ai, J Yamagishi 2021 IEEE Spoken Language Technology Workshop (SLT), 734-741, 2021 | 3 | 2021 |
| Exploring Effective Speech Representation via ASR for High-Quality End-to-End Multispeaker TTS D Liu, L Wang, S Li, H Li, C Ding, J Zhang, J Dang International Conference on Neural Information Processing, 110-118, 2021 | 2 | 2021 |
| Joint Noise Reduction and Listening Enhancement for Full-End Speech Enhancement H Li, Y Liu, J Yamagishi arXiv preprint arXiv:2203.11500, 2022 | 1 | 2022 |
