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Metodologia para cuantificar los efectos perceptuales de los sistemas de supresion del ruido

Methodology is proposed for perceptual assessment of both subjective sound quality & speech recognition in such way that results can be compared between these two aspects. Validation is performed with a noise suppression system applied to hearing instruments. A method termed Interpolated Paired...

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Bibliographic Details
Published in:International journal of audiology 2005-12, Vol.44 (12), p.721-732
Main Authors: Dahlquist, Martin, Lutman, Mark E, Wood, Sally, Leijon, Arne
Format: Article
Language:English
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Summary:Methodology is proposed for perceptual assessment of both subjective sound quality & speech recognition in such way that results can be compared between these two aspects. Validation is performed with a noise suppression system applied to hearing instruments. A method termed Interpolated Paired Comparison Rating (IPCR) was developed for time efficient assessment of subjective impression of different aspects of sound quality for a variety of noise conditions. The method is based on paired comparisons between processed and unprocessed stimuli, and the results are expressed as the difference in signal-to-noise ratio (dB) between these that give equal subjective impression. For tests of speech recognition in noise, validated adaptive test methods can be used that give results in terms of speech-to-noise ratio. The methodology was shown to be sensitive enough to detect significant mean differences between processed and unprocessed speech in noise recognition ability in groups consisting of 30 subjects. An effect on sound quality from the noise suppression equivalent to about 3-4 dB is required to be statistically significant for a single subject. A corresponding effect of 3-6 dB is required for speech recognition (one-sided test). The magnitude of difference that occurred in the present study for sound quality was sufficient to show significant differences for sound quality within individuals, but this was not the case for speech recognition. Adapted from the source document.
ISSN:1499-2027
DOI:10.1080/14992020500271712