An improved competing voices test for test of attention

Authors

  • Lars Bramsløw Eriksholm Research Centre, Snekkersten, Denmark
  • Marianna Vatti Eriksholm Research Centre, Snekkersten, Denmark
  • Rikke Rossing Eriksholm Research Centre, Snekkersten, Denmark
  • Niels Henrik Pontoppidan Eriksholm Research Centre, Snekkersten, Denmark

Keywords:

audiology, speech, competing speech, test method

Abstract

People with hearing impairment find competing voices scenarios to be challenging in terms of their ability to switch attention and adapt to the situation. With the Competing Voices Test (CVT), we can explore how they can adapt and change their attention between voices. The CVT provides three male and three female speakers, played in pairs. The task of the listener is to repeat the target sentence. Three methods of cueing the listener to the target sentence were tested: a male/female cue (for male-female sentence pairs), an audio voice cue and a text cue using one word from the target sentence. The cue was presented either before or after the sentence pair playback. The CVT was evaluated on 14 moderate-severely hearing impaired listeners with four spatial conditions: summed (diotic), separate (dichotic) plus two types of ideal masks for separating the two speakers from the sum. The results show that the test is sensitive to the spatial conditions, as intended. The text cue is the most sensitive to spatial condition. The text cue has the further advantage that it can be used for, e.g., male-male speaker pairs as well. Furthermore, the applied ideal masks show test scores very close to the ideal separate spatial condition.

References

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Additional Files

Published

2017-12-18

How to Cite

Bramsløw, L., Vatti, M., Rossing, R., & Pontoppidan, N. H. (2017). An improved competing voices test for test of attention. Proceedings of the International Symposium on Auditory and Audiological Research, 6, 279–286. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2017-34

Issue

Section

2017/5. Speech perception: Behavioral measures and modelling