2014•Unpublished venueRequires access

Development of sound source estimation techniques using binaural sound — Creation of self-organizing maps by real-time data

Kikuo Fujimura, Nishioka Ken, Isao Nakanishi, Shigang Li

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Abstract

We are developing a technology to detect the orientation of the sound source, distance and type using the binaural acoustic signal using a microphone at least two. This has a long study of binaural sound, a period in the 1970s was a hot topic. At that time, it was only a simple analog signal processing circuit, there was a disadvantage of not being able to correspond only to the ideal model. Therefore, it is difficult to extract information such as the orientation with high accuracy from the signal obtained in a real environment, including the reflected sound. In this paper we report that actually sound collection from vehicles traveling in the binaural acoustic signal, we have succeeded in creating a self-organizing map for determining the type of vehicle using the data.

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What this paper is about

We are developing a technology to detect the orientation of the sound source, distance and type using the binaural acoustic signal using a microphone at least two. This has a long study of binaural sound, a period in the 1970s was a hot topic. At that time, it was only a simple analog signal processing circuit, there was a disadvantage of not being able to correspond only to the ideal model. Therefore, it is difficult to extract information such as the orientation with high accuracy from the signal obtained in a real environment, including the reflected sound. In this paper we report that actually sound collection from vehicles traveling in the binaural acoustic signal, we have succeeded in creating a self-organizing map for determining the type of vehicle using the data.

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Available abstract

We are developing a technology to detect the orientation of the sound source, distance and type using the binaural acoustic signal using a microphone at least two. This has a long study of binaural sound, a period in the 1970s was a hot topic. At that time, it was only a simple analog signal processing circuit, there was a disadvantage of not being able to correspond only to the ideal model. Therefore, it is difficult to extract information such as the orientation with high accuracy from the signal obtained in a real environment, including the reflected sound. In this paper we report that actually sound collection from vehicles traveling in the binaural acoustic signal, we have succeeded in creating a self-organizing map for determining the type of vehicle using the data.

Key concepts: Binaural recording, Computer science, SIGNAL (programming language), Sound (geography), Acoustics, Microphone, Acoustic source localization, Audio signal processing

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