Computationally Efficient Fixed-Filter ANC for Speech Based on Long-Term Prediction for Headphone Applications

Yurii Iotov, Sidsel Marie Nørholm, Valiantsin Belyi, Mads Dyrholm, Mads Græsbøll Christensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)
74 Downloads (Pure)

Abstract

In some situations, such as open office spaces, speech can play the role of an unwanted and disturbing source of noise, and ANC headphones or earbuds might help to solve this problem. However, ANC in modern headphones is often based on a pre-calculated fixed-filter for practical reasons, like stability and cost. Moreover, in some cases the optimal filter is non-causal, which cannot be realized with such a filter, and ANC attenuation performance will be significantly decreased. In this paper we propose to solve the causality problem in feedforward fixed-filter ANC systems by integrating a long-term linear prediction filter to predict the incoming disturbance, here speech, by the same amount of samples ahead in time, as the non-causal delay. The proposed ANC system outperforms conventional adaptive feedforward ANC systems in terms of computational complexity, showing comparable or better results on voiced speech attenuation at non-causal delays from 4 to 18 samples (0.5 to 2.25 ms) at a sampling frequency of 8 kHz.
Original languageEnglish
Title of host publication2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
Number of pages5
PublisherIEEE
Publication date2022
Pages761-765
ISBN (Print)978-1-6654-0541-6
ISBN (Electronic)978-1-6654-0540-9
DOIs
Publication statusPublished - 2022
Event47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
Duration: 23 May 202227 May 2022

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/TerritorySingapore
CityVirtual, Online
Period23/05/202227/05/2022
SponsorChinese and Oriental Languages Information Processing Society (COLPIS), Singapore Exhibition and Convention Bureau, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), The Institute of Electrical and Electronics Engineers Signal Processing Society
SeriesI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149

Bibliographical note

Funding agency: 10.13039/100017413-Innovation Fund

Keywords

  • ANC headphones
  • Causality
  • Fixed-filter ANC
  • Long-term linear prediction
  • Speech attenuation

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