Speech Summarization of Long Spoken Document: Improving Memory Efficiency of Speech/Text Encoders-Reference-Cited by-同舟云学术

Speech Summarization of Long Spoken Document: Improving Memory Efficiency of Speech/Text Encoders

Published:2023-06-04 Issue: Volume: Page:
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Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Kano Takatomo¹,Ogawa Atsunori¹,Delcroix Marc¹,Sharma Roshan²,Matsuura Kohei¹,Watanabe Shinji²

Affiliation:

1. NTT Corporation,Japan

2. Carnegie Mellon University,Pittsburgh,USA

Publisher

IEEE

Link

Reference29 articles.

1. ROUGE: A package for automatic evaluation of summaries;lin;ACL,2004

2. Longformer: The long-document transformer;beltagy;ArXiv,2020

4. How2: A large-scale dataset for multimodal language understanding;sanabria;ArXiv,2018

5. Big bird: Transformers for longer sequences;zaheer;NIPS,2020

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2. Train Long and Test Long:Leveraging Full Document Contexts in Speech Processing;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14