Követés
Xuankai Chang
Xuankai Chang
Apple - Carnegie Mellon University
E-mail megerősítve itt: apple.com
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
7472021
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
3062020
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
2782021
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
1162019
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
1112024
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
1032020
Recognizing multi-talker speech with permutation invariant training
D Yu, X Chang, Y Qian
arXiv preprint arXiv:1704.01985, 2017
1012017
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
942018
Single-channel multi-talker speech recognition with permutation invariant training
Y Qian, X Chang, D Yu
Speech Communication 104, 1-11, 2018
842018
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
832022
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
822019
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
792021
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
762021
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
702022
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
532021
Unrestricted Vocabulary Keyword Spotting Using LSTM-CTC.
Y Zhuang, X Chang, Y Qian, K Yu
Interspeech, 938-942, 2016
532016
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
482023
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
462022
Investigation of end-to-end speaker-attributed ASR for continuous multi-talker recordings
N Kanda, X Chang, Y Gaur, X Wang, Z Meng, Z Chen, T Yoshioka
2021 IEEE Spoken Language Technology Workshop (SLT), 809-816, 2021
422021
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
372023
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