Near and Far Field Speech-in-Noise Intelligibility Improvements Based on a Time-Frequency Energy Reallocation Approach

Tudor Catalin Zorila, Yannis Stylianou, Tatsuma Ishihara, Masami Akamine

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

An algorithm designed to enhance the intelligibility of speech signals before they are presented in noisy environments was evaluated. The processed and unprocessed speech had the same root-mean square level. Spectral energy was redistributed to increase the signal-to-noise ratio (SNR) in the mid-and high-frequency bands, while the softer segments of speech were increased in level by applying time-domain dynamic range compression. Noise level adaptation was introduced to increase the subjective quality of signals at high SNRs. Evaluations were conducted both in near field (headphones) and in far field (outdoor) conditions using listeners with normal hearing and two types of background. The results showed: (a) In the near field test, the proposed algorithm yielded significant intelligibility improvements relative to the unprocessed speech for both stationary and nonstationary backgrounds; (b) In the far field test, the proposed algorithm increased the intelligibility of unprocessed speech by a factor of seven at 200-m distance from the sound source; and (c) When the background level did not alter intelligibility, listeners preferred the quality of the speech processed by the noise-dependent version of the algorithm.

Original languageEnglish
Pages (from-to)1808-1818
Number of pages11
JournalIEEE/ACM Transactions on Audio Speech and Language Processing
Volume24
Issue number10
DOIs
Publication statusPublished - 2016 Oct
Externally publishedYes

Keywords

  • Dynamic range compression
  • Spectral shaping
  • public address system
  • speech intelligibility enhancement

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Acoustics and Ultrasonics
  • Computational Mathematics
  • Electrical and Electronic Engineering

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