Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences
In studies investigating binaural processing in human listeners, relatively long and task-dependent time constants of a binaural window ranging from 10 ms to 250 ms have been observed. Such time constants are often thought to reflect “binaural sluggishness.” In this study, the effect of binaural slu...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2018-01-01
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| Series: | Trends in Hearing |
| Online Access: | https://doi.org/10.1177/2331216517753547 |
| _version_ | 1818035581686382592 |
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| author | Christopher F. Hauth Thomas Brand |
| author_facet | Christopher F. Hauth Thomas Brand |
| author_sort | Christopher F. Hauth |
| collection | DOAJ |
| description | In studies investigating binaural processing in human listeners, relatively long and task-dependent time constants of a binaural window ranging from 10 ms to 250 ms have been observed. Such time constants are often thought to reflect “binaural sluggishness.” In this study, the effect of binaural sluggishness on binaural unmasking of speech in stationary speech-shaped noise is investigated in 10 listeners with normal hearing. In order to design a masking signal with temporally varying binaural cues, the interaural phase difference of the noise was modulated sinusoidally with frequencies ranging from 0.25 Hz to 64 Hz. The lowest, that is the best, speech reception thresholds (SRTs) were observed for the lowest modulation frequency. SRTs increased with increasing modulation frequency up to 4 Hz. For higher modulation frequencies, SRTs remained constant in the range of 1 dB to 1.5 dB below the SRT determined in the diotic situation. The outcome of the experiment was simulated using a short-term binaural speech intelligibility model, which combines an equalization–cancellation (EC) model with the speech intelligibility index. This model segments the incoming signal into 23.2-ms time frames in order to predict release from masking in modulated noises. In order to predict the results from this study, the model required a further time constant applied to the EC mechanism representing binaural sluggishness. The best agreement with perceptual data was achieved using a temporal window of 200 ms in the EC mechanism. |
| first_indexed | 2024-12-10T06:57:20Z |
| format | Article |
| id | doaj.art-25e59f50e04745a094b6bb9472b0d837 |
| institution | Directory Open Access Journal |
| issn | 2331-2165 |
| language | English |
| last_indexed | 2024-12-10T06:57:20Z |
| publishDate | 2018-01-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Trends in Hearing |
| spelling | doaj.art-25e59f50e04745a094b6bb9472b0d8372022-12-22T01:58:24ZengSAGE PublishingTrends in Hearing2331-21652018-01-012210.1177/2331216517753547Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase DifferencesChristopher F. Hauth0Thomas Brand1Cluster of Excellence Hearing4All, Carl von Ossietzky Universität, Oldenburg, GermanyCluster of Excellence Hearing4All, Carl von Ossietzky Universität, Oldenburg, GermanyIn studies investigating binaural processing in human listeners, relatively long and task-dependent time constants of a binaural window ranging from 10 ms to 250 ms have been observed. Such time constants are often thought to reflect “binaural sluggishness.” In this study, the effect of binaural sluggishness on binaural unmasking of speech in stationary speech-shaped noise is investigated in 10 listeners with normal hearing. In order to design a masking signal with temporally varying binaural cues, the interaural phase difference of the noise was modulated sinusoidally with frequencies ranging from 0.25 Hz to 64 Hz. The lowest, that is the best, speech reception thresholds (SRTs) were observed for the lowest modulation frequency. SRTs increased with increasing modulation frequency up to 4 Hz. For higher modulation frequencies, SRTs remained constant in the range of 1 dB to 1.5 dB below the SRT determined in the diotic situation. The outcome of the experiment was simulated using a short-term binaural speech intelligibility model, which combines an equalization–cancellation (EC) model with the speech intelligibility index. This model segments the incoming signal into 23.2-ms time frames in order to predict release from masking in modulated noises. In order to predict the results from this study, the model required a further time constant applied to the EC mechanism representing binaural sluggishness. The best agreement with perceptual data was achieved using a temporal window of 200 ms in the EC mechanism.https://doi.org/10.1177/2331216517753547 |
| spellingShingle | Christopher F. Hauth Thomas Brand Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences Trends in Hearing |
| title | Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences |
| title_full | Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences |
| title_fullStr | Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences |
| title_full_unstemmed | Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences |
| title_short | Modeling Sluggishness in Binaural Unmasking of Speech for Maskers With Time-Varying Interaural Phase Differences |
| title_sort | modeling sluggishness in binaural unmasking of speech for maskers with time varying interaural phase differences |
| url | https://doi.org/10.1177/2331216517753547 |
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