@inproceedings{d6b6387434f44cc1af1533c87c945ed3,
title = "CATSLU: The 1st Chinese audio-textual spoken language understanding challenge",
abstract = "Spoken language understanding (SLU) is a key component of conversational dialogue systems, which converts user utterances into semantic representations. The previous works almost focus on parsing semantic from textual inputs (top hypothesis of speech recognition and even manual transcripts) while losing information hidden in the audio. We herein describe the 1st Chinese Audio-Textual Spoken Language Understanding Challenge (CATSLU) which introduces a new dataset with audio-textual information, multiple domains and domain knowledge. We introduce two scenarios of audio-textual SLU in which participants are encouraged to utilize data of other domains or not. In this paper, we will describe the challenge and results.",
keywords = "Datasets, Spoken language understanding",
author = "Su Zhu and Zijian Zhao and Tiejun Zhao and Chengqing Zong and Kai Yu",
note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 21st ACM International Conference on Multimodal Interaction, ICMI 2019 ; Conference date: 14-10-2019 Through 18-10-2019",
year = "2019",
month = oct,
day = "14",
doi = "10.1145/3340555.3356098",
language = "英语",
series = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
publisher = "Association for Computing Machinery, Inc",
pages = "521--525",
editor = "Wen Gao and \{Ling Meng\}, \{Helen Mei\} and Matthew Turk and Fussell, \{Susan R.\} and Bjorn Schuller and Bjorn Schuller and Yale Song and Kai Yu",
booktitle = "ICMI 2019 - Proceedings of the 2019 International Conference on Multimodal Interaction",
}