Skip to main content

Performance of speech enhancement algorithms on the speech intelligibility of native Mandarin listeners immersed in English-speaking environment

Buy Article:

$15.00 + tax (Refund Policy)

Speech enhancement algorithms have been developed to improve speech intelligibility for listeners under noisy conditions. However, all existing algorithms were evaluated only by native listeners, the performance of such algorithms on non-native listeners was rarely investigated. This study conducts a subjective listening test on native New Zealand English listeners and native Mandarin listeners who have been immersed in New Zealand English-speaking environment for more than one year. The participants were asked to transcribe noisy English sentences processed by five widely used single-channel speech enhancement algorithms. The speech intelligibility of the two groups was quantified and compared to investigate the effectiveness of the speech enhancement algorithms on non-native listeners who are familiar with the target language.

The requested document is freely available to subscribers. Users without a subscription can purchase this article.

Sign in

Document Type: Research Article

Affiliations: 1: Acoustics Research Centre, Department of Mechanical and Mechatronics Engineering, University of Auckland 2: Department of Electrical, Computer and Software Engineering, University of Auckland

Publication date: 30 November 2023

More about this publication?
  • The Noise-Con conference proceedings are sponsored by INCE/USA and the Inter-Noise proceedings by I-INCE. NOVEM (Noise and Vibration Emerging Methods) conference proceedings are included. All NoiseCon Proceedings one year or older are free to download. InterNoise proceedings from outside the USA older than 10 years are free to download. Others are free to INCE/USA members and member societies of I-INCE.

  • Membership Information
  • INCE Subject Classification
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content