Environmental sound classification using log-Gabor filter
Abstract
This paper presents novel approaches for efficient feature extraction using environmental sound magnitude spectrogram. We propose approaches based on the visual domain, the spectrogram is passed through a bank of 12 log-Gabor filters, followed by an averaged operation and passed through an optimal feature selection procedure based on mutual information. The proposed methods were tested on a database of 10 sound classes. The evaluation system is realized by using the multiclass support vector machines (SVM's) that gave rise to a recognition rate of the order 89.62 %.
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Some recent methods in acoustic processing use Gabor-filter banks on sound spectra as a preprocessing step and achieve accurate results on acoustic processing tasks such as classification of environmental sounds, music genre recognition, and speech analysis.
“some recent methods in acoustic processing use Gabor-filter banks on the sound spectra as a preprocessing step, achieving accurate results on acoustic processing tasks, such as the classification of environmental sounds [41], music genre recognition [42], and speech analysis [43,44], to cite a few”
From A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance (2022) · cites this paper as [41]
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Domingos, L. C. F., Santos, P. E., Skelton, P. S. M., Brinkworth, R. S. A., & Sammut, K. (2022) · Sensors · doi:10.3390/s22062181 · Cited by 93 · see citing works
“on acoustic processing tasks, such as the classification of environmental sounds [41], music genre recognition [42], and speech analysis [43,44], to cite a few.”
Background
- Authors
- Souli, S., & Lachiri, Z.
- Affiliations
- National Engineering School of Tunis (TN)
- ORCID
- Lachiri, Zied
- Venue
- 2012 IEEE 11th International Conference on Signal Processing
- Publisher
- IEEE
- Published
- 2012-10
- Pages
- 144-147
- OpenAlex
- W2064219851
- Cited by
- 3
- References
- 0
- Citations by year
- 2024: 1 · 2022: 1 · 2017: 1
- FWCI
- 0.00
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Keywords
- environmental sound classification, log-Gabor filters, magnitude spectrogram, feature extraction, mutual information feature selection, support vector machine, sound event recognition
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