Customized Wake-Word Integration in ANC-Enabled Headphones: Enhancing Assistive Technology for Noise-Sensitive Employees in Office

This paper explores the personalization of wake words in Active Noise Cancelling (ANC) enabled headphones designed as assistive technology for noise-sensitive individuals. We focus on the incorporation and assessment of intended wake words, categorizing them based on fillers and first names. Given the language-dependent nature of this approach, our research primarily addresses the English language. We propose an evaluation mechanism to determine the efficacy of potential wake words, predicting their recognition accuracy and length. The study involves a comparative analysis between combinations of fillers and first names, aiming to identify the optimal pairing. We offer recommendations on the best-performing combinations, enhancing the reliability and user experience of ANC headphones as a supportive tool for noise-sensitive individuals. Our findings aim to provide a robust framework for developing highly responsive and personalized wake word systems, tailored to the unique needs of noise-sensitive individuals in office environments.

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Publication Details

Published
2024-08-26
DOI
https://doi.org/10.1145/3670653.3677489
Primary Topic
Noise Effects and Management
Type
article
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Customized Wake-Word Integration in ANC-Enabled Headphones: Enhancing Assistive Technology for Noise-Sensitive Employees in Office

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Noise Effects and Management
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Customized Wake-Word Integration in ANC-Enabled Headphones: Enhancing Assistive Technology for Noise-Sensitive Employees in Office

David Gollasch, Jan Schmalfuß-Schwarz, Gerhard Weber, Meinhardt Branig, Christin Engel
article en

Abstract

This paper explores the personalization of wake words in Active Noise Cancelling (ANC) enabled headphones designed as assistive technology for noise-sensitive individuals. We focus on the incorporation and assessment of intended wake words, categorizing them based on fillers and first names. Given the language-dependent nature of this approach, our research primarily addresses the English language. We propose an evaluation mechanism to determine the efficacy of potential wake words, predicting their recognition accuracy and length. The study involves a comparative analysis between combinations of fillers and first names, aiming to identify the optimal pairing. We offer recommendations on the best-performing combinations, enhancing the reliability and user experience of ANC headphones as a supportive tool for noise-sensitive individuals. Our findings aim to provide a robust framework for developing highly responsive and personalized wake word systems, tailored to the unique needs of noise-sensitive individuals in office environments.

Technische Universität Dresden (DE)
Openalex Percentile: Top 78%
Noise Effects and Management
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