MFCCA:Multi-Frame Cross-Channel Attention for Multi-Speaker ASR in Multi-Party Meeting Scenario
Author:
Affiliation:
1. School of Computer Science, Northwestern Poly technical University,Audio, Speech and Language Processing Group (ASLP@NPU),Xi'an,China
2. College of Computer Science and Technology, Zhejiang University,Hangzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10022052/10022330/10022715.pdf?arnumber=10022715
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1. The Second Multi-Channel Multi-Party Meeting Transcription Challenge (M2MeT 2.0): A Benchmark for Speaker-Attributed ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16
2. Sa-Paraformer: Non-Autoregressive End-To-End Speaker-Attributed ASR;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16
3. End-to-End Multichannel Speaker-Attributed ASR: Speaker Guided Decoder and Input Feature Analysis;2023 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU);2023-12-16
4. SURT 2.0: Advances in Transducer-Based Multi-Talker Speech Recognition;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023
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