Final Project: Sound Source Localization

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1 Final Project: Sound Source Localization Warren De La Cruz/Darren Hicks Physics 2P April 27,

2 1 Abstract The purpose of this project will be to create an auditory system analogous to a pair of human ears. In animal auditory systems, the method of determining the location of a sound source is the Interaural Time Difference (ITD) cue in the auditory cortex of the brain. The ITD is the time difference between the arrival of the signal at the first ear, and the arrival of the signal at the second ear. Consequently, this results in an Interaural Phase Difference (IPD) between the signals at each ear. Assuming the origin of the sound is a point source, the intensity at some distance R from the source can be determined as where clearly, we can see that, I = P πr 2 I 1 πr 2 Since the microphones will be at different radial distances from the sound source, there should then be distinct level differences between both signals. For this particular project, the operation of the device can be described as sound source localization. This shall be accomplished by an arrangement of two microphones placed equal distances from a pivot point rotated by a servo motor, which we can refer to as the origin. A sound source, placed some distance in front of the device, will emit a continuous audio signal that can be picked up by the microphones. When the audio signals reaches a predetermined trigger voltage (b/w 2.5-5V) at either microphone, then data accumulation begins for both microphone channels simultaneously. To ensure a precise output we require the time between the collection of each data point to be sufficiently small ( 10 s). This will allow for more reliable waveform analysis, thus, more accurately pinpointing the extrema of each input signal. If we consider the microphone array as the x-axis then the phase shift determined from the waveforms corresponds to the angular rotation from the positive y-axis, also known as the azimuth. We then rotate the microphone array through this azimuth; thus orienting the device to the sound source. Problem we encountered included low and high frequency input signal noise, Input signal noise was dealt with by restricting the range of frequencies available for analysis,achieved by implementing the appropriate bandpass filter. Writing the appropriate algorithm for analyzing input data also proved to be trouble. The actual device as proposed was not realistic and in its place, a simpler high frequency tracking device was created, making small adjustments based on comparison of 2 averaged data samples. 2

3 2 Introduction The motivation for this project was to create a device which would be useful in tracking a sound source, in particular, rotate to essentially follow a person while they moved around, speaking. After peer review of the proposed idea, the project was reduced in order to realistically accomplish some sort of acoustic localization. The device ultimately was restricted make small adjustments in reaction to the incoming signal of a high frequency source, in the range of kHz. 3 Hardware The device is composed of; 50cm rod Maple wood base LM358 dual amplifier equiped with high pass filters (attenuating input of f <1kHz) Futaba S3152 Digital Servo Motor Damping foam inside neck of device to reduce mechanical vibrations. Figure 1: The Device. 3

4 4 Software Figure 2: Software Algorithm Flowchart 4

5 Initially, the idea was to compare the timing of both signals for each microphone and based on their time difference, the rod would rotate the appropriate amount. The PIC assembly language, however, cannot process two signals simultaneously. As a result of this, there would be an associated time delay between collecting the data for each microphone. Instead we opted for a more approximate brute force method which would determine the average intensity of 16 samples taken at each microphone. A simple subtraction can then compare the two intensities, and depending on which signal is determined to be higher, the microphone array would rotate itself either clockwise or counterclockwise, in small increments. The device was also meant to cease movement upon achieving a condition such that the incoming signals from the microphones are approximately equal. The software algorithm can be seen in figure 1 on the previous page. The servo was driven using a pulse loop (PlsLoop), driven by the pulse loop counter (PLC). Its purpose was to run through a loop X number of times in order to produce the appropriately timed pulse width signal to the servo motor. It is based on the nop command which essentially wastes a full instruction cycle(200ns). Each cycle of the pulse loop would be 10 5 seconds and PLC would be a number corresponding to 100x the pulse width, in ms. 5 Discussion Hardware difficulties encountered in the initial phases of the project involved trying to minimize, and ideally eliminate noise from the input signals. Unfiltered, all audible frequencies incident on the microphones would stimulate a response from the device. In order to eliminate high frequency buzzing from affecting the operation of the device, we required the inclusion of low-pass filters on the positive terminal of the microphone. In order to eliminate lower frequency rumblings, we included a high pass filter such that input signals less than 1kHz were attenuated. The original plan was to use an ultrasonic frequency as the source, but the speaker used was not able to output such frequencies. Furthermore, even in a silent environment, there would be low voltage fluctuations across the microphones. However, in the software, 3 right-shifts of the ADC value stored in the PIC board s memory created a low enough precision that eliminated such fluctations. Software difficulties involved troubles with enforcing limits on the pulse loop counter, along with issues arising from processing the data. In the early stages of the software s development, there was absolutely no response of the system to signals to the microphone. Instead, the code involved at the time would change the value of the pulsewidth by arbitrary values, creating rotating motion similar to that of an automated lawn sprinkler. This was simply an error in the ordering of certain commands, and was rectified fairly swiftly. The next large issue to arise was the erratic nature of the device to input signals. The code was initially written to simply add 4 samples together and compare the values between the left and right microphones. This proved to be clearly inaccurate, so the number of samples was quadrupled, and the values were averaged before comparison. Also, the signal on one particular microphone was generally always higher than the other, regardless of source position; causing the device to always tend to one direction. This was dealt with by 5

6 reducing the precision of the ADC value, as described above. The operation of the project, although not what was originally intended, was a success on a more basic level, tracking a monochromatic sound source at approximately 1m in front of the device. With further time, the performance of the device could have been made more efficient; its movement smoother. 6

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