11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

A Speech-in-Noise Test Based on Spoken Digits: Comparison of Normal and Impaired Listeners Using a Computer Model

Matthew Robertson (1), Guy J. Brown (1), Wendy Lecluyse (2), Manasa Panda (2), Christine M. Tan (2)

(1) University of Sheffield, UK
(2) Essex University, UK

This paper describes a speech-in-noise test which is suitable for testing both human and machine speech recognition in noise. The test uses spoken digit triplets, presented in a range of babble backgrounds and signal-to-noise ratios (SNRs). The performance of a normal hearing (NH) and hearing impaired (HI) listener have been assessed using the test. Both listeners show a fall in performance with decreasing SNR, as well as a decrease in performance with an increase in the number of talkers in the babble background. A physiologically accurate computational auditory model has been tuned to match the NH and HI listeners, allowing their performance in the test to be modelled using a missing data-based automatic speech recognition (ASR) system. For the NH model we show a good match to the behaviour of the human listener. However, the computer model underestimates the digit test performance of the specific HI listener considered here.

Full Paper

Bibliographic reference.  Robertson, Matthew / Brown, Guy J. / Lecluyse, Wendy / Panda, Manasa / Tan, Christine M. (2010): "A speech-in-noise test based on spoken digits: comparison of normal and impaired listeners using a computer model", In INTERSPEECH-2010, 2470-2473.