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Scaling Studies of Perceived Source Width

Juha Merimaa Institut für Kommunikationsakustik Ruhr-Universität Bochum. Scaling Studies of Perceived Source Width. Outline. Introduction Background on listening tests Description of the conducted pilot test Analysis methods & preliminary results Discussion & summary. Introduction.

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Scaling Studies of Perceived Source Width

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  1. Juha Merimaa Institut für KommunikationsakustikRuhr-Universität Bochum Scaling Studies of Perceived Source Width

  2. Outline • Introduction • Background on listening tests • Description of the conducted pilot test • Analysis methods & preliminary results • Discussion & summary

  3. Introduction • A room or a hall broadens the perceived width of auditory objects • Traditionally auditory source width (ASW) has been investigated as a descriptor for concert halls • How does the broadening depend on source signals?

  4. In other words... • In a scene based paradigm • source broadening is due to the part of room effect that is grouped with source signals • the rest of room effect is resolved into a separate percept • What are the spatial features related to auditory “deconvolution” of reverberation

  5. Listening test basics • Quantifying auditory perception • Levels of measurement Nominal Ordinal Short Long 2 3 1 Interval Ratio 0 1 2 3 4 0 1 2 3 4

  6. Possible test methods for assessing ASW • Direct scaling • Rating • Rank ordering • Assigning stimuli in successive categories • Constant reference • All stimuli are judged relative to a single reference stimulus

  7. Possible test methods (contd.) • Method of adjustment • Listeners adjust a variable reference to correspond to each stimulus • Adaptive procedures • Reference is adaptively adjusted based on listeners judgements • Pairwise comparisons • Each stimulus is judged relative to all others

  8. Why pairwise comparisons? • Source broadening is expected to be a sum of several interaural signal features • All except pairwise comparison methods force the results onto a linear scale • Weighting of dimensions implicit in the data • Can be accessed with factor analysis • Weights may vary between individuals, which will result in noisy unidimensional data

  9. Pilot listening test • Gathering both preference and distance data between pairs

  10. Two harmonic complexes,f0 = 196 Hz, -12 dB/oct No modulation (h1) Freq. mod. 1%, 6 Hz (h2) Pink noise 100 Hz –10 kHz (ns) Stimuli • Anechoic samples convolved with binaural room responses • Speech (sp) • Cello, f0 = 196 Hz(ce) • Snare drum (sn)

  11. Binaural room responses • Diffuse field and system compensated responses • Medium size diffuse concert hall (p) • RT = 2.2 s, 1-IACCE3 = 0.78 • Large multipurpose hall (a) • RT = 2.4 s, 1-IACCE3 = 0.02 • Small listening room (s) • RT = 0.5 s, 1-IACCE3 = 0.32

  12. Altogether 18 stimuli resulting in 153 permutations

  13. Analysis of preference data • A single run comparing all the the pairs results in a preference matrix that can be used to rank order the stimuli • In an ideal case each run will yield the same perfectly ordered set of data A B C D A B 1 C 0 0 D 1 1 1

  14. Real world comparative judgements • Each stimulus has a dispersion on a psychological scale • Each judgment of distance and order depend on current points of perception

  15. Checking for consistency • Circular triads • Mean for random answerswith 18 stimuli: 204 • Average in collected data approx. 40 • All data matrices consistent with significance p < 0.01 B A C

  16. Unidimensional scaling • Simplest scaling method: count the number of times a single stimulus is prefered over all others

  17. Wincount statistics, CR = 60

  18. Comparison with stimulus IACC

  19. More sophisticated scaling • Thurstone's law provides a method for mapping pair comparison data on an interval scale • Assumes normally distributed unidimensional data • Includes tests for checking the fit • Results • Significance of deviation from data p < 0.01

  20. Multidimensional scaling • Uses distances between stimuli to construct a spatial representation ofdata in n dimensions • Metric (interval) and nonmetric (ordinal) procedures • Few assumptions on data • Works well with a relatively small number of test subjects

  21. 3-D scaling of all stimuli 1.5 s_h1 a_h2 a_sn 1 a_ns p_ns a_h1 0.5 p_sp a_sp s_h2 0 p_h2 a_ce p_sn -0.5 p_ce p_h1 s_sp s_sn s_ce -1 s_ns -1.5 2 -2 -1 0 0 1 2 -2 3

  22. Comparison of the large halls

  23. Multipurpose hall vs. Listening room

  24. Concert hall vs. Listening room p_ns 2 1.5 s_ce 1 s_sp s_h2 p_sp p_h2 0.5 p_h1 p_sn 0 p_ce s_sn -0.5 s_ns -1 s_h1 2 -1.5 0 -2 -2 -1 0 1 -2 2

  25. Discussion & conclusions • The perception of auditory source width is clearly multidimensional • Results between the most similar spaces suggest separate source and room dimensions with some interaction • Euclidian metric of MDS might not reflect human perception between extreme cases • The pilot data is insufficient to draw more firm conclusions

  26. Future work • A larger listening test with a reduced set of stimuli • Interpreting the dimensions in terms of binaural cues • Breaking the experiment into several unidimensional studies • Use gained results in choosing stimuli • Similar investigations into envelopment

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