Challenges and Opportunities in Multi-device Speech Processing
Gregory Ciccarelli, Jarred Barber, Arun Nair, Israel Cohen, Tao Zhang
TL;DR
This paper reviews the current state, challenges, and future prospects of multi-device speech processing technologies, emphasizing the need for new datasets and solutions in smart home environments.
Contribution
It provides a comprehensive overview of technical challenges, existing solutions, and future directions in multi-device speech processing, highlighting gaps and opportunities for research.
Findings
Identifies key technical challenges in multi-device speech recognition
Highlights the need for specialized datasets for multi-device scenarios
Provides an outlook on future research directions in the field
Abstract
We review current solutions and technical challenges for automatic speech recognition, keyword spotting, device arbitration, speech enhancement, and source localization in multidevice home environments to provide context for the INTERSPEECH 2022 special session, "Challenges and opportunities for signal processing and machine learning for multiple smart devices". We also identify the datasets needed to support these research areas. Based on the review and our research experience in the multi-device domain, we conclude with an outlook on the future evolution
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Taxonomy
TopicsSpeech Recognition and Synthesis · Speech and Audio Processing · Music and Audio Processing