The effect of situation-specific non-speech acoustic cues on the intelligibility of speech in noise

Lauren Ward, Ben Shirley, Yan Tang, William J. Davies

Research output: Contribution to journalConference articlepeer-review

Abstract

In everyday life, speech is often accompanied by a situation-specific acoustic cue; a hungry bark as you ask 'Has anyone fed the dog?'. This paper investigates the effect such cues have on speech intelligibility in noise and evaluates their interaction with the established effect of situation-specific semantic cues. This work is motivated by the introduction of new object-based broadcast formats, which have the potential to optimise intelligibility by controlling the level of individual broadcast audio elements, at point of service. Results of this study show that situation-specific acoustic cues alone can improve word recognition in multi-talker babble by 69.5%, a similar amount to semantic cues. The combination of both semantic and acoustic cues provide further improvement of 106.0% compared with no cues, and 18.7% compared with semantic cues only. Interestingly, whilst increasing subjective intelligibility of the target word, the presence of acoustic cues degraded the objective intelligibility of the speech-based semantic cues by 47.0% (equivalent to reducing the speech level by 4.5 dB). This paper discusses the interactions between the two types of cues and the implications that these results have for assessing and improving the intelligibility of broadcast speech.

Original languageEnglish (US)
Pages (from-to)2958-2962
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2017-August
DOIs
StatePublished - Jan 1 2017
Externally publishedYes
Event18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017 - Stockholm, Sweden
Duration: Aug 20 2017Aug 24 2017

Keywords

  • Broadcast media
  • Intelligibility
  • Speech perception

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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