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Prior listening exposure to a reverberant room improves open-set intelligibility of high-variability sentences
1. Boila, R. S. , Nelson, W. T. , Ericson, M. A. , and Simpson, B. D. (2000). “A speech corpus for multitalker communications research,” J. Acoust. Soc. Am. 107(2), 1065–1066.
2. Brandewie, E. J. , and Zahorik, P. (2010). “Prior listening in rooms improves speech intelligibility,” J. Acoust. Soc. Am. 128(1), 291–299.
3. Felty, R. (2008). “Perceptually robust English sentence test (open-set),” Unpublished manuscript, Indiana University, Bloomington, IN.
4. Garofolo, J. , Lamel, L. F. , Fisher, W. M. , Fiscus, J. G. , Pallett, D. S. , Dahlgren, N. L. , and Zue, V. (1993). “DARPA TIMIT acoustic-phonetic continuous speech corpus,” Linguistic Data Consortium, Philadelphia, PA.
5. Gilbert, J. L. , Tamati, T. N. , and Pisoni, D. B. (2013). “Development, reliability, and validity of PRESTO: A new high-variability sentence recognition test,” J. Am. Acad. Audiol. 24, 1–11.
6. Helfer, K. S. , and Wilber, L. A. (1990). “Hearing loss, aging, and speech perception in reverberation and noise,” J. Speech Hear. Res. 33(1), 149–155.
9. Nabelek, A. K. , and Mason, D. (1981). “Effect of noise and reverberation on binaural and monaural word identification by subjects with various audiograms,” J. Speech Hear. Res 24(2), 375–383.
11. Plomp, R. (1976). “Binaural and monaural speech intelligibility of connected discourse in reverberation as a function of azimuth of a single competing sound source (speech or noise),” Acustica 34, 200–211.
12. Srinivasan, N. K. , and Zahorik, P. (2011). “The effect of semantic context on speech intelligibility in reverberant rooms,” Proc. Meet. Acoust. 12, 060001.
13. Studebaker, G. A. (1985). “A rationalized arcsine transform,” J. Speech Hear. Res. 28(3), 455–462.
14. Tamati, T. N. , Gilbert, J. L. , and Pisoni, D. B. (2013). “Some factors underlying individual differences in speech recognition on PRESTO: A first report,” J. Am. Acad. Audiol. In press.
15. Watkins, A. J. (2005a). “Perceptual compensation for effects of echo and of reverberation on speech identification,” Acta Acust. 91, 892–901.
16. Watkins, A. J. (2005b). “Perceptual compensation for effects of reverberation in speech identification,” J. Acoust. Soc. Am. 118(1), 249–262.
17. Watkins, A. J. , and Makin, S. J. (2007). “Steady-spectrum contexts and perceptual compensation for reverberation in speech identification,” J. Acoust. Soc. Am. 121(1), 257–266.
18. Watkins, A. J. , Raimond, A. P. , and Makin, S. J. (2011). “Temporal-envelope constancy of speech in rooms and the perceptual weighting of frequency bands,” J. Acoust. Soc. Am. 130(5), 2777–2788.
19. Zahorik, P. (2009). “Perceptually relevant parameters for virtual listening simulation of small room acoustics,” J. Acoust. Soc. Am. 126(2), 776–791.
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Previous studies have demonstrated that speech understanding in reverberant rooms improves when listeners are given prior exposure to the room. Results from these room-adaptation studies are limited, however, because they were conducted with materials that are not representative of the high acoustic variability observed in speech signals during everyday communication. Here, room adaptation effects were measured using an open-set speech corpus with high lexical and indexical variability and virtual auditory space techniques to simulate binaural listening in rooms. Room adaptation effects of comparable magnitude to previous studies were observed, suggesting general importance for facilitating speech intelligibility in reverberation.
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