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Overview of the ICASSP 2023 General Meeting Understanding and Generation Challenge (MUG)

arXiv 2303.13932 ↗First posted 24 Mar 2023cs.CL cs.SD eess.AScited by 0

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Abstract (arXiv)

ICASSP2023 General Meeting Understanding and Generation Challenge (MUG) focuses on prompting a wide range of spoken language processing (SLP) research on meeting transcripts, as SLP applications are critical to improve users' efficiency in grasping important information in meetings. MUG includes five tracks, including topic segmentation, topic-level and session-level extractive summarization, topic title generation, keyphrase extraction, and action item detection. To facilitate MUG, we construct and release a large-scale meeting dataset, the AliMeeting4MUG Corpus.

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References · 5

  1. 2020Longformer: The Long-Document Transformercited by 3,413
  2. 2019StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understandingcited by 109
  3. 2020PALM: Pre-training an Autoencoding&Autoregressive Language Model for Context-conditioned Generationcited by 42
  4. 2021PoNet: Pooling Network for Efficient Token Mixing in Long Sequencescited by 5
  5. 2023W2KPE: Keyphrase Extraction with Word-Word Relationcited by 2

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