Kaggle Competition: Cantonese Audio-Visual Speech Recognition for In-car Commands

• URL: http://arxiv.org/abs/2207.02663v1
• Date: Wed, 6 Jul 2022 13:31:56 GMT
• Title: Kaggle Competition: Cantonese Audio-Visual Speech Recognition for In-car Commands
• Authors: Wenliang Dai, Samuel Cahyawijaya, Tiezheng Yu, Elham J Barezi, Pascale Fung
• Abstract summary: In-car smart assistants should be able to process general as well as car-related commands. Most datasets are in major languages, such as English and Chinese. We propose Cantonese Audio-Visual Speech Recognition for In-car Commands.
• Score: 48.155806720847394
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: With the rise of deep learning and intelligent vehicles, the smart assistant has become an essential in-car component to facilitate driving and provide extra functionalities. In-car smart assistants should be able to process general as well as car-related commands and perform corresponding actions, which eases driving and improves safety. However, in this research field, most datasets are in major languages, such as English and Chinese. There is a huge data scarcity issue for low-resource languages, hindering the development of research and applications for broader communities. Therefore, it is crucial to have more benchmarks to raise awareness and motivate the research in low-resource languages. To mitigate this problem, we collect a new dataset, namely Cantonese In-car Audio-Visual Speech Recognition (CI-AVSR), for in-car speech recognition in the Cantonese language with video and audio data. Together with it, we propose Cantonese Audio-Visual Speech Recognition for In-car Commands as a new challenge for the community to tackle low-resource speech recognition under in-car scenarios.

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