2. Department of Electrical & Computer Engineering Auditory Perception Meena Ramani 04/09/2004

3. Department of Electrical & Computer Engineering Note For this lecture many of the slides will be accompanied by scanned pictures shown on the OHP from Zwicker and Fastl’s “Psycho-acoustics facts and models” 2 nd edition

4. Department of Electrical & Computer Engineering Main Outline Anatomy of the Ear and Hearing DONE Auditory perception Hearing aids and Cochlear implants. Extra: Direction of Arrival Estimation

5. Department of Electrical & Computer Engineering Auditory perception Shepard Tones Masking Ohms Acoustic Law Critical Bands Webers law Just Noticeable Frequency

6. Department of Electrical & Computer Engineering Roger PenroseM.C. Escher Ascending and Descending Optical Illusion Audio Illusion

7. Department of Electrical & Computer Engineering Shepard Tones Circularity in Judgments of Relative Pitch, Roger N. Shepard, JASA 1964. –Sensitivity to descending pitch –Sensitivity to volume changes between these pitches. A set of eight tones all an octave apart The tones simultaneously descend in pitch till half of their original pitch. Jump back up to their original pitch and repeat the cycle. Perceive this change? Unique volume curve Effect: Seamless transition in the cycle. It’s all in your head! Omit two of the eight tones in the mid frequency range.

8. Department of Electrical & Computer Engineering You know I can't hear you when the water is running! MASKINGMASKING

9. Department of Electrical & Computer Engineering Masking Low-frequency, broad banded sounds (like water running) will mask higher frequency sounds which are softer at the listener's ear (a conversational tone from across the room). –Example 2: Truck in street Masking occurs because two frequencies lie within a critical band and the higher amplitude one masks the lower amplitude signal. Masking can be because of broad band, narrowband noise, pure and complex tones. Masking threshold –Amount of dB for test tone to be just audible in presence of noise See OHP Figure

10. Department of Electrical & Computer Engineering Masking by Broad band noise White noise- frequency independent PSD Masked thresholds are a function of frequency. Low and very high frequency almost same as TOQ. Above 500Hz, thresholds increase with increase in frequency Increasing white noise by 10dB increases masked threshold up by 10dB for frequencies >500Hz. =>Linear behavior of masking NOTE: TOQ’s frequency dependence almost completely disappears  Ear’s frequency selectivity and critical bands. See OHP Figure

11. Department of Electrical & Computer Engineering Masking by Narrow band noise Narrow band <=Critical BW Noise (constant Amplitude, Different Frequency) –0.25,1,4KHz –BW: 100, 160, 700Hz –60dB Frequency dependence of threshold masked by 250Hz seems to be broader Maximum value of masked threshold is lower for higher frequencies. Steep increase but flatter decrease See OHP Figure

12. Department of Electrical & Computer Engineering Masking by Narrow band noise (cont) Noise (Varying Amplitude, Fixed Frequency) –1KHz noise –20-100dB Slope of rise seems independent of Amplitude But slope of fall is dependent on amplitude Non-Linear frequency dependence Strange effect at high masker amplitudes: –At high amplitudes ear begins to listen to anything audible!! –Begin to hear difference noise (noise and testing tone) See OHP Figure

13. Department of Electrical & Computer Engineering Masking by Pure and Complex tones Pure tones: –Below threshold of Quiet of test tone can hear only masking tone –Above it <700hZ can hear both –From 900-10kHz can hear only masking tone though above threshold of hearing for test tone. –Between 1-2kHz difference tones are also audible –Low level masker  wider at low frequencies –High level maskers  wider at high frequencies Complex tones: –Log scale distance between the partials has a larger difference at LF, less difference at HF –Dips correspondingly become smaller as frequency increases –2 octaves above highest spectral content curve approaches TOQ See OHP Figure

14. Department of Electrical & Computer Engineering Temporal Aspects of Masking Previously assume long lasting test and masking sounds Speech has a strong temporal structure Vowels --loudest parts Consonants faint Often plosive consonants are masked by preceding loud vowel

15. Department of Electrical & Computer Engineering Temporal Aspects of Masking (cont) Simultaneous Masking Pre-Stimulus/Backward/Premasking –1 st test tone 2 nd Masker Poststimulus/Forward/Postmasking –1 st Masker 2 nd test tone

16. Department of Electrical & Computer Engineering Types of Masking Simultaneous masking –Duration less than 200ms test tone threshold increases with decrease in duration. –Duration >200ms constant test tone threshold –Assume hearing system integrates over a period of 200ms Postmasking (100ms) –Decay in effect of masker 100ms –More dominant Premasking (20ms) –Takes place before masker is on!! –Each sensation is not instantaneous, requires build-up time Quick build up for loud maskers Slower build up for softer maskers –Less dominant effect See OHP Figure

17. Department of Electrical & Computer Engineering Ohm’s Acoustic Law The sound quality of a complex tone depends ONLY on the amplitudes and NOT relative phases of its harmonics.

18. Department of Electrical & Computer Engineering Critical Bands Proposed by Fletcher Noise which masks a test tone is the part of its spectrum which lies near the tone Masking is achieved when the power of the tone and the power of the noise spectrum lying near the tone and masking it are the same. Bands defined this way have a BW which produces same acoustic power in the tone and in the noise in the band when the tone is masked.  CRITICAL BANDS See OHP Figure

19. Department of Electrical & Computer Engineering Critical Band (cont.) How to measure? –Masking of a band pass noise using 2 tones CB corresponds with1.5mm spacing on BM. 24 such band pass filters BW of the filters increases with increasing center frequency Logarithmic relationship  Weber’s law example. Bark scale See OHP Figure

20. Department of Electrical & Computer Engineering Webers law Weber's Law states that the ratio of the increment threshold to the background intensity is a constant. So when you are in a noisy environment you must shout to be heard while a whisper works in a quiet room. when you measure increment thresholds on various intensity backgrounds, the thresholds increase in proportion to the background.

21. Department of Electrical & Computer Engineering Just noticeable change in Frequency (Pg:183) Similar to variation in the critical band structure This is because it depends on number of BPFs More BPF better resolution Till about 500Hz JND is about 3.6Hz. After 500Hz it varies as 0.007f See OHP Figure

22. Department of Electrical & Computer Engineering HEARING AIDS

23. Department of Electrical & Computer Engineering Outline Facts on hearing loss Cell phones and hearing loss Types of Hearing aid Inside a hearing aid Audiogram

24. Department of Electrical & Computer Engineering Facts on Hearing Loss in Adults One in every ten (28 million) Americans has hearing loss. The vast majority of Americans (95% or 26 million) with hearing loss can have their hearing loss treated with hearing aids. Only 5% of hearing loss in adults can be improved through medical or surgical treatment Millions of Americans with hearing loss could benefit from hearing aids but avoid them because of the stigma.

25. Department of Electrical & Computer Engineering Cell phones and Hearing aids Cell Phones emit a type of electromagnetic energy that interferes with the operation of hearing aids. The Federal Communications Commission in mid-July 2003 ordered the cell phone industry to help out the hard-of-hearing. “Within two years, cell-phone manufacturers must offer at least two phones with reduced interference for each type of cellular technology used, or ensure that one-fourth of phones the carriers sell produce less interference.” The FCC’s final milestone is February 2008.

26. Department of Electrical & Computer Engineering Types of Hearing aids Behind The ear In the Ear In the Canal Completely in the canal

27. Department of Electrical & Computer Engineering Anatomy of a Hearing Aid Microphone Tone hook Volume control On/off switch Battery compartment

28. Department of Electrical & Computer Engineering Inside a Hearing aid 1: The microphone The microphone picks up sound waves from the air and transforms them into electrical signals. 2: The microphone suspension The microphone suspension holds the microphone in place. 3: The loudspeaker The loudspeaker sends the amplified sounds into your ear. The loudspeaker is also called the receiver and sometimes the telephone. 4: The battery drawer The battery drawer holds the battery in place. 5: The amplifier The amplifier makes the signals that come from the microphone louder. 6: The telecoil The telecoil makes it possible for you to hear one specific person if you are in a place that supports the use of a telecoil. Many classrooms, churches and cinemas have telecoil. The telecoil makes it possible for you to hear i.e. your teacher without hearing the noise around you. It is also possible to use the telecoil at home - with the TV or the radio.

29. Department of Electrical & Computer Engineering Audiograms

30. Department of Electrical & Computer Engineering Direction of Arrival (DOA) estimation algorithm

31. Department of Electrical & Computer Engineering Talk outline Necessity for DOA DOA algorithm Requirements Types of DOA algorithms –Delay and sum –Minimum variance –MUSIC –Coherent MUSIC –Root MUSIC –ESPRIT Comparison Measures Computational Intensity comparison Accuracy Comparison Accuracy vs Computational intensity Conclusion

32. Department of Electrical & Computer Engineering Where does the DOA come into the picture? Has 2 microphones DOA Estimation  s  n Beamformer Lets meet at 11?!? 7 is good for me too!! 11 sounds good!!

33. Department of Electrical & Computer Engineering Direction of Arrival Estimation Algorithms The DOA algorithm must satisfy the following conditions : – Low computational intensity (MIPS/MFLOPS) – High accuracy (RMSE) – High speed – Easy implementation – Good performance at low SNRs – Works on a 2 microphone array system with 4cm separation between them.

34. Department of Electrical & Computer Engineering DOA Algorithms Spatial Correlation methods Subspace decomposition methods MUSIC Multiple Signal Estimation ESPRIT Estimation of Signal parameters using rotational invariance Delay and SumMinimum Variance Coherent MUSIC Root MUSIC

35. Department of Electrical & Computer Engineering DOA MethodEquation for Implementation Delay and Sum Minimum Variance MUSIC Coherent MUSIC Root MUSIC ESPRIT

36. Department of Electrical & Computer Engineering Comparison Measures To evaluate the computational intensity –MFLOPS comparison plot To evaluate the accuracy –Root Mean Square Error comparison plot To evaluate the effect at low SNRs –SNR vs Estimated angle plot To evaluate overall performance –Accuracy vs computational intensity

37. Department of Electrical & Computer Engineering Evaluation of computational Intensity: MFLOPS comparison chart Min Variance 0.93 Mflops Coherent MUSIC 0.3958 Mflops DS 0.3573 Mflops MUSIC 0.0813 Mflops ESPRIT 0.0086 Mflops Root MUSIC 0.0068 Mflops

38. Department of Electrical & Computer Engineering Comparison of accuracy at different SNR values

39. Department of Electrical & Computer Engineering Comparison of Accuracy-MFLOPS

40. Department of Electrical & Computer Engineering Conclusion Tradeoff between Accuracy and Computational intensity leads to the conclusion that ESPRIT is the Direction of arrival estimation algorithm best suited for our purpose MFLOPS value: 0.0086 RMSE value:~3 (at 10dB)

41. Department of Electrical & Computer Engineering