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Spatial unmasking of nearby pure-tone sources in a simulated anechoic environment

Spatial unmasking of nearby pure-tone sources in a simulated anechoic environment. Norbert Kopco Hearing Research Center and Cognitive and Neural Systems Dept Boston University. Objectives.

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Spatial unmasking of nearby pure-tone sources in a simulated anechoic environment

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  1. Spatial unmasking of nearby pure-tone sources in a simulated anechoic environment Norbert Kopco Hearing Research Center and Cognitive and Neural Systems Dept Boston University

  2. Objectives • How do unique acoustical properties of sources near the head influence listener’s ability to detect masked sounds? (monaural vs. binaural cues, informational masking, distance-related cues) • Can available models of auditory processing explain observed performance? • Baseline for future studies of unmasking of nearby complex/speech sources and reverberation. Spatial unmasking of nearby pure-tone sources

  3. Overview • Background • Methods • Data - Spatial Unmasking • Monaural and Binaural Factors • Binaural Unmasking - Analysis/Modeling • Independence of Responses in Adaptive Procedures Spatial unmasking of nearby pure-tone sources

  4. Background • Spatial separation of target from noise improves target detectability and intelligibility. • Typically studied under two experimental conditions: • headphone studies: • address question: “What acoustic (monaural or binaural) cues are used to detect masked signal and how (by what mechanisms) are the cues extracted?” • plenty of data (summarized in Durlach & Colburn, 1978), many conditions • mostly done under fairly artificial conditions (flat noise spectrum, no noise ILD) • data predicted well from models of binaural auditory processing • studies in real environment: • address questions:“Are non-acoustic (informational) cues (e.g., perceived direction) important for detection of masked signals?”“What is relative importance of different cues (and the mechanisms that extract them) in real listening situations?” • relatively few, studying unmasking of:- pure tones (Ebata et al., 1968; Santon, 1987; Doll et al., 1992),- noise bursts (Saberi et al., 1991; Good et al., 1997), - auditory patterns (Kidd et al., 1998), and - speech (Freyman et al., 1999; Hawley et al., 1999) Spatial unmasking of nearby pure-tone sources

  5. Background • Acoustic cues for nearby sources: • large ILDs at all frequencies • small positional changes cause large cue changes • ILDs vary with both direction and distance • analyzed by Brungart et al. (1998), Shinn-Cunningham et al. (2000) • Current state in understanding of spatial unmasking: • past studies results can be explained by a combination of acoustic (monaural, binaural) and informational (un)masking • no studies of spatial unmasking for nearby sources • no quantitative modeling of spatial unmasking • no studies of unmasking as a function of source distance • available headphone data • cannot be used to predict unmasking at all spatial combinations of tone and masker (few data with masker ILD) • no complete set of data for single subjects available Spatial unmasking of nearby pure-tone sources

  6. Present study • Goals: • Measure spatial unmasking of pure tones for nearby sources in simulated anechoic auditory space • Compare relative importance of monaural and binaural processing for unmasking • Study significance of the distance dimension for spatial unmasking (only monaural effects as in far field, or also binaural effects?) • Compare behavioral data with predictions of available models • Relation to previous studies • of spatial unmasking: • virtual auditory environment  better control of parameters  possible modeling • weaker percept of spatial position • headphone studies of binaural unmasking (and modeling): • masker shaped by HRTF  better spatial percept • masker spectrum not flat  possible challenge for modeling Spatial unmasking of nearby pure-tone sources

  7. Methods • Simulated anechoic auditory spacenear the listener • 60 target/masker configurations • individually measured HRTFs • T: 500 or 1000 Hz, 165 ms • M: 250 ms white noise, lowpass at 5000 Hz • TDT equipment • 3-down-1-up adaptive procedure (79.4%) • 3 repetitions for each measurement (+ additional as needed) • 3 blocks of 6 sessions, each session has 10 runs Spatial unmasking of nearby pure-tone sources

  8. Spatial Unmasking Spatial unmasking of nearby pure-tone sources

  9. Monaural Factors Spatial unmasking of nearby pure-tone sources

  10. Binaural Factors Spatial unmasking of nearby pure-tone sources

  11. Binaural Unmasking - Data Spatial unmasking of nearby pure-tone sources

  12. Binaural Unmasking at 500 Hz Spatial unmasking of nearby pure-tone sources

  13. Binaural Unmasking - Stern & Shear Spatial unmasking of nearby pure-tone sources

  14. p and R function at 500 Hz Spatial unmasking of nearby pure-tone sources

  15. Binaural Unmasking - Stern&Shear fit Spatial unmasking of nearby pure-tone sources

  16. Independence of Responses • One of assumptions in adaptive procedures is that there is no dependence between responses in consecutive trials • During the experiment, subjects react differently depending on feedback: • negative feedback worsens performance • Possible reasons: • change in subject’s concentration depending on feedback • subject’s learning of the adaptive procedure • Is the effect significant? • How does it influence the measured thresholds? Spatial unmasking of nearby pure-tone sources

  17. t-test of Significance • 1. For every spatial configuration estimate psychometric function at points with sufficient number of measurements • 2. Compute difference between psychometric functions given correct vs. incorrect response for all spatial configs and levels Spatial unmasking of nearby pure-tone sources

  18. t-test of Significance • H0: E{ p(c | previous c) - p(c | previous not c)} = 0 • N M1-M2 tobs p • 500 Hz S1 405 3.66 2.185 0.015 REJECT • 500 Hz S2 383 0.86 0.533 0.297 • 500 Hz S3 370 0.80 0.480 0.316 • 1000 Hz S1 407 3.88 2.259 0.012 REJECT • 1000 Hz S2 388 0.17 0.108 0.457 • 1000 Hz S3 343 -4.74 -3.098 0.001 REJECT • 500 Hz x-S 1158 1.82 1.907 0.028 REJECT • 1000 Hz x-S 1138 0.02 0.018 0.493 • x-freq x-subj 2296 0.93 1.381 0.084 • Test how does the largest observed difference influence the measured thresholds. Spatial unmasking of nearby pure-tone sources

  19. Simulation of response dependence • The value of swas estimated to be 10.1. • Simulation of subj S3 on 1000 Hz: M1-M2=-4.74, s=10.1, 10000 trials. • Feedback-determined difference of 5% leads to error in determined threshold smaller • than 0.5 dB. Spatial unmasking of nearby pure-tone sources

  20. Conclusions • from spatial unmasking point of view: • large spatial unmasking for nearby anechoic sources (-15 to 40 dB) • can be modeled very accurately using available models of auditory processing • source distance influences amount of binaural unmasking of nearby sources • monaural (better-ear) effects prevail (25 dB) • binaural processing important at lower frequencies and for masker near midline (10 dB) • binaural unmasking comparable for near and far sources • from point of view of modeling binaural auditory processing: • original Colburn (1977) p(ITD,fc) function better than Stern & Shear (1996) version at 500 Hz • to fit the 1000 Hz data Stern & Shear (1996) version of p(ITD,fc) function, or R(ILD) function, needs to be refined • if masker spectrum doesn’t deviate dramatically from flat shape, it can be sufficiently approximated by f0-centered ERB (error within 1dB) • transformed adaptive procedures: • assumption of independence between responses can be often broken, but this has small influence on the measured thresholds (up to 0.5 dB in this study) • future work: • unmasking of complex sounds/speech, effect of reverberation Spatial unmasking of nearby pure-tone sources

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