Paper
Sound Classification for Hearing Aids Using Time-frequency Images
- Authors:
- Koji Abe; Hiroyoshi Masaki; Haiyan Tian
- Abstract
- This paper presents a method for extracting features of real sound data from time-frequency images. The features are used for a sound classification equipped for hearing aids. As an application of hearing aids in mind, four classes of “classical music”, “speech”, “multi-talker noise”, and “speech in the noise” are prepared in order to classify the input signal of a hearing aid into useful classes. Although there are several possible ways to figure out which class the current input signal belongs to, an approach from image processing is utilized to find out appropriate features because 2D image (time-frequency image) can contain multifaceted information compared to 1D information (waveform or frequency response of sound), and can be regarded as comprehensive data. It is found that eight features are required to meet a certain quality of sound classification according to our investigation. Experimental results of the sound classification by some clustering machines using the proposed features have shown that accuracy of the classification was more than 95% with every clustering machine.
- Keywords
- Hearing Aids; Sound Classification; Auditory Scene Analysis; Time-Frequency Image
- StartPage
- 159
- EndPage
- 166
- Doi