LSTM based similarity measurement with spectral clustering for speaker diarization Q Lin, R Yin, M Li, H Bredin, C Barras arXiv preprint arXiv:1907.10393, 2019 | 126 | 2019 |
Atss-net: Target speaker separation via attention-based neural network T Li, Q Lin, Y Bao, M Li arXiv preprint arXiv:2005.09200, 2020 | 42 | 2020 |
The dku-dukeece-lenovo system for the diarization task of the 2021 voxceleb speaker recognition challenge W Wang, D Cai, Q Lin, L Yang, J Wang, J Wang, M Li arXiv preprint arXiv:2109.02002, 2021 | 32 | 2021 |
Self-attentive similarity measurement strategies in speaker diarization. Q Lin, Y Hou, M Li INTERSPEECH, 284-288, 2020 | 23 | 2020 |
Towards lightweight applications: Asymmetric enroll-verify structure for speaker verification Q Li, L Yang, X Wang, X Qin, J Wang, M Li ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 22 | 2022 |
DIHARD II is still hard: Experimental results and discussions from the DKU-LENOVO team Q Lin, W Cai, L Yang, J Wang, J Zhang, M Li arXiv preprint arXiv:2002.12761, 2020 | 22 | 2020 |
Similarity measurement of segment-level speaker embeddings in speaker diarization W Wang, Q Lin, D Cai, M Li IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 2645-2658, 2022 | 20 | 2022 |
Low-latency online speaker diarization with graph-based label generation Y Zhang, Q Lin, W Wang, L Yang, X Wang, J Wang, M Li arXiv preprint arXiv:2111.13803, 2021 | 15 | 2021 |
The DKU Speech Activity Detection and Speaker Identification Systems for Fearless Steps Challenge Phase-02. Q Lin, T Li, M Li INTERSPEECH, 2607-2611, 2020 | 14 | 2020 |
Sparsely overlapped speech training in the time domain: Joint learning of target speech separation and personal vad benefits Q Lin, L Yang, X Wang, L Xie, C Jia, J Wang 2021 Asia-Pacific Signal and Information Processing Association Annual …, 2021 | 13 | 2021 |
Online target speaker voice activity detection for speaker diarization W Wang, Q Lin, M Li arXiv preprint arXiv:2207.05920, 2022 | 12 | 2022 |
The DKU-Duke-Lenovo system description for the third DIHARD speech diarization challenge W Wang, Q Lin, D Cai, L Yang, M Li arXiv preprint arXiv:2102.03649, 2021 | 6 | 2021 |
Optimal Mapping Loss: A Faster Loss for End-to-End Speaker Diarization. Q Lin, T Li, L Yang, J Wang, M Li Odyssey, 125-131, 2020 | 5 | 2020 |
The DKU-Duke-Lenovo System Description for the Fearless Steps Challenge Phase III. W Wang, D Cai, J Wang, Q Lin, X Wang, M Hong, M Li Interspeech, 1044-1048, 2021 | 2 | 2021 |