Enhancing Chinese tone recognition by manipulating amplitude envelope: implications for cochlear implants

J Acoust Soc Am. 2004 Dec;116(6):3659-67. doi: 10.1121/1.1783352.

Abstract

Tone recognition is important for speech understanding in tonal languages such as Mandarin Chinese. Cochlear implant patients are able to perceive some tonal information by using temporal cues such as periodicity-related amplitude fluctuations and similarities between the fundamental frequency (F0) contour and the amplitude envelope. The present study investigates whether modifying the amplitude envelope to better resemble the F0 contour can further improve tone recognition in multichannel cochlear implants. Chinese tone and vowel recognition were measured for six native Chinese normal-hearing subjects listening to a simulation of a four-channel cochlear implant speech processor with and without amplitude envelope enhancement. Two algorithms were proposed to modify the amplitude envelope to more closely resemble the F0 contour. In the first algorithm, the amplitude envelope as well as the modulation depth of periodicity fluctuations was adjusted for each spectral channel. In the second algorithm, the overall amplitude envelope was adjusted before multichannel speech processing, thus reducing any local distortions to the speech spectral envelope. The results showed that both algorithms significantly improved Chinese tone recognition. By adjusting the overall amplitude envelope to match the F0 contour before multichannel processing, vowel recognition was better preserved and less speech-processing computation was required. The results suggest that modifying the amplitude envelope to more closely resemble the F0 contour may be a useful approach toward improving Chinese-speaking cochlear implant patients' tone recognition.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Algorithms
  • Cochlear Implants*
  • Female
  • Humans
  • Language*
  • Male
  • Phonetics
  • Pitch Perception*
  • Prosthesis Design
  • Sound Spectrography
  • Speech Acoustics*
  • Speech Perception*