| Superb: Speech processing universal performance benchmark S Yang, PH Chi, YS Chuang, CIJ Lai, K Lakhotia, YY Lin, AT Liu, J Shi, ... arXiv preprint arXiv:2105.01051, 2021 | 987 | 2021 |
| CHiME-6 challenge: Tackling multispeaker speech recognition for unsegmented recordings S Watanabe, M Mandel, J Barker, E Vincent, A Arora, X Chang, ... arXiv preprint arXiv:2004.09249, 2020 | 373 | 2020 |
| Recent developments on espnet toolkit boosted by conformer P Guo, F Boyer, X Chang, T Hayashi, Y Higuchi, H Inaguma, N Kamo, C Li, ... ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 304 | 2021 |
| Audiogpt: Understanding and generating speech, music, sound, and talking head R Huang, M Li, D Yang, J Shi, X Chang, Z Ye, Y Wu, Z Hong, J Huang, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 23802 …, 2024 | 193 | 2024 |
| MIMO-Speech: End-to-end multi-channel multi-speaker speech recognition X Chang, W Zhang, Y Qian, J Le Roux, S Watanabe 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019 | 129 | 2019 |
| Uniaudio: An audio foundation model toward universal audio generation D Yang, J Tian, X Tan, R Huang, S Liu, X Chang, J Shi, S Zhao, J Bian, ... arXiv preprint arXiv:2310.00704, 2023 | 121 | 2023 |
| End-to-end multi-speaker speech recognition with transformer X Chang, W Zhang, Y Qian, J Le Roux, S Watanabe ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 116 | 2020 |
| Recognizing multi-talker speech with permutation invariant training D Yu, X Chang, Y Qian arXiv preprint arXiv:1704.01985, 2017 | 111 | 2017 |
| Past review, current progress, and challenges ahead on the cocktail party problem Y Qian, C Weng, X Chang, S Wang, D Yu Frontiers of Information Technology & Electronic Engineering 19, 40-63, 2018 | 108 | 2018 |
| SUPERB-SG: Enhanced speech processing universal performance benchmark for semantic and generative capabilities HS Tsai, HJ Chang, WC Huang, Z Huang, K Lakhotia, S Yang, S Dong, ... arXiv preprint arXiv:2203.06849, 2022 | 102 | 2022 |
| ESPnet-SE: End-to-end speech enhancement and separation toolkit designed for ASR integration C Li, J Shi, W Zhang, AS Subramanian, X Chang, N Kamo, M Hira, ... 2021 IEEE Spoken Language Technology Workshop (SLT), 785-792, 2021 | 97 | 2021 |
| Single-channel multi-talker speech recognition with permutation invariant training Y Qian, X Chang, D Yu Speech Communication 104, 1-11, 2018 | 95 | 2018 |
| End-to-end monaural multi-speaker ASR system without pretraining X Chang, Y Qian, K Yu, S Watanabe ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 91 | 2019 |
| An exploration of self-supervised pretrained representations for end-to-end speech recognition X Chang, T Maekaku, P Guo, J Shi, YJ Lu, AS Subramanian, T Wang, ... 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2021 | 89 | 2021 |
| Espnet-slu: Advancing spoken language understanding through espnet S Arora, S Dalmia, P Denisov, X Chang, Y Ueda, Y Peng, Y Zhang, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 81 | 2022 |
| The chime-7 dasr challenge: Distant meeting transcription with multiple devices in diverse scenarios S Cornell, M Wiesner, S Watanabe, D Raj, X Chang, P Garcia, ... arXiv preprint arXiv:2306.13734, 2023 | 63 | 2023 |
| Ml-superb: Multilingual speech universal performance benchmark J Shi, D Berrebbi, W Chen, HL Chung, EP Hu, WP Huang, X Chang, ... arXiv preprint arXiv:2305.10615, 2023 | 63 | 2023 |
| Voxtlm: Unified decoder-only models for consolidating speech recognition, synthesis and speech, text continuation tasks S Maiti, Y Peng, S Choi, J Jung, X Chang, S Watanabe ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 59 | 2024 |
| End-to-end integration of speech recognition, speech enhancement, and self-supervised learning representation X Chang, T Maekaku, Y Fujita, S Watanabe arXiv preprint arXiv:2204.00540, 2022 | 59 | 2022 |
| The 2020 espnet update: new features, broadened applications, performance improvements, and future plans S Watanabe, F Boyer, X Chang, P Guo, T Hayashi, Y Higuchi, T Hori, ... 2021 IEEE Data Science and Learning Workshop (DSLW), 1-6, 2021 | 57 | 2021 |
Shinji WatanabeCarnegie Mellon UniversityZweryfikowany adres z cmu.edu