Pals, C. (2008) Detection and Recognition Threshold of Sound Sources in Noise. Master's Thesis / Essay, Artificial Intelligence.
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Abstract
This study examines detection and recognition thresholds for environmental sounds in the presence of noise. Human listeners were presented with a selection of everyday sounds masked by noise at different signal-to-noise ratios (SNR). Participants had to indicate if they detected or recognized the sound in the masking noise. Different categorizations of the sounds were compared. Results show that pulse-like sounds are detected at a lower maximum local SNR than noise-like sounds. For one categorization we found detection of tonal sounds at a lower maximum local SNR than noise-like sounds. For another categorization we found detection of pulse-like sounds at a lower maximum local SNR than tonal sounds. These differences in detection between pulse-like, tonal and noiselike sounds suggest human auditory perception combines different strategies for detecting these sound types.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Degree programme: | Artificial Intelligence |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:45 |
| Last Modified: | 15 Feb 2018 07:45 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/9521 |
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