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Binaural sound localizer for azimuthal movement detection based on diffraction.

Kim K, Choi A - Sensors (Basel) (2012)

Bottom Line: The gradient analysis of the ILD between the structured and unstructured microphone demonstrates the rotation directions as clockwise, counter clockwise, and no rotation of the sound source.Acoustic experiments with different types of sound source over a wide range of target movements show that the average true positive and false positive rates are 67% and 16%, respectively.Spectral analysis demonstrates that the low frequency delivers decreased true and false positive rates and the high frequency presents increases of both rates, overall.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics & Electrical Engineering, Dongguk University-Seoul, Seoul 100-715, Korea. kwkim@dongguk.edu

ABSTRACT
Sound localization can be realized by utilizing the physics of acoustics in various methods. This paper investigates a novel detection architecture for the azimuthal movement of sound source based on the interaural level difference (ILD) between two receivers. One of the microphones in the system is surrounded by barriers of various heights in order to cast the direction dependent diffraction of the incoming signal. The gradient analysis of the ILD between the structured and unstructured microphone demonstrates the rotation directions as clockwise, counter clockwise, and no rotation of the sound source. Acoustic experiments with different types of sound source over a wide range of target movements show that the average true positive and false positive rates are 67% and 16%, respectively. Spectral analysis demonstrates that the low frequency delivers decreased true and false positive rates and the high frequency presents increases of both rates, overall.

No MeSH data available.


Spectrum of sound sources.
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f14-sensors-12-10584: Spectrum of sound sources.

Mentions: Previous analysis is performed based on the white noise signal, which is fabricated by the normally distributed random numbers, for structure verification and parameter estimation. To evaluate the RDD system, the realistic sound data representing the conventional situation is required for statistical analysis. The general sound from outdoor field is most likely to change the spectrum over time; therefore, the stationary spectrum is devised to execute the experiments in order to derive statistically consistent outcome. Four sound sources selected are airplane, helicopter, car, and jet airplane which are recorded at the fixed location over the moving object. Range of time data that corresponds to the clear representation of acoustic characteristic is used as the FIR filter coefficient for generating the stationary sound source based on the white input signal. The spectrum of the given data set is illustrated in Figure 14. The frequency distribution of the airplane and helicopter demonstrates the relatively narrow band signal concentrated on the low frequency region. On the other hand, car and jet airplane spectrum displays extensive distribution of the power over the wide frequency range. Therefore, the individual sound source denotes the distinctive spectrum sound for improving the diversity of the experiment. Also, note that the volume of each signal is unified at the time of wave creation.


Binaural sound localizer for azimuthal movement detection based on diffraction.

Kim K, Choi A - Sensors (Basel) (2012)

Spectrum of sound sources.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472845&req=5

f14-sensors-12-10584: Spectrum of sound sources.
Mentions: Previous analysis is performed based on the white noise signal, which is fabricated by the normally distributed random numbers, for structure verification and parameter estimation. To evaluate the RDD system, the realistic sound data representing the conventional situation is required for statistical analysis. The general sound from outdoor field is most likely to change the spectrum over time; therefore, the stationary spectrum is devised to execute the experiments in order to derive statistically consistent outcome. Four sound sources selected are airplane, helicopter, car, and jet airplane which are recorded at the fixed location over the moving object. Range of time data that corresponds to the clear representation of acoustic characteristic is used as the FIR filter coefficient for generating the stationary sound source based on the white input signal. The spectrum of the given data set is illustrated in Figure 14. The frequency distribution of the airplane and helicopter demonstrates the relatively narrow band signal concentrated on the low frequency region. On the other hand, car and jet airplane spectrum displays extensive distribution of the power over the wide frequency range. Therefore, the individual sound source denotes the distinctive spectrum sound for improving the diversity of the experiment. Also, note that the volume of each signal is unified at the time of wave creation.

Bottom Line: The gradient analysis of the ILD between the structured and unstructured microphone demonstrates the rotation directions as clockwise, counter clockwise, and no rotation of the sound source.Acoustic experiments with different types of sound source over a wide range of target movements show that the average true positive and false positive rates are 67% and 16%, respectively.Spectral analysis demonstrates that the low frequency delivers decreased true and false positive rates and the high frequency presents increases of both rates, overall.

View Article: PubMed Central - PubMed

Affiliation: Division of Electronics & Electrical Engineering, Dongguk University-Seoul, Seoul 100-715, Korea. kwkim@dongguk.edu

ABSTRACT
Sound localization can be realized by utilizing the physics of acoustics in various methods. This paper investigates a novel detection architecture for the azimuthal movement of sound source based on the interaural level difference (ILD) between two receivers. One of the microphones in the system is surrounded by barriers of various heights in order to cast the direction dependent diffraction of the incoming signal. The gradient analysis of the ILD between the structured and unstructured microphone demonstrates the rotation directions as clockwise, counter clockwise, and no rotation of the sound source. Acoustic experiments with different types of sound source over a wide range of target movements show that the average true positive and false positive rates are 67% and 16%, respectively. Spectral analysis demonstrates that the low frequency delivers decreased true and false positive rates and the high frequency presents increases of both rates, overall.

No MeSH data available.