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Title

A Clustering-Based Approach for Features Extraction in Spectro-Temporal Domain Using Artificial Neural Network

Year: 1400
COI: JR_IJE-34-2_017
Language: EnglishView: 51
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Authors

N. Esfandian - Department of Electrical Engineering, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
K. Hosseinpour - Department of Artificial Intelligence and Robotics, Aryan Institute of Higher Education and Technology, Babol, Iran

Abstract:

In this paper, a new feature extraction method is presented based on spectro-temporal representation of speech signal for phoneme classification. In the proposed method, an artificial neural network approach is used to cluster spectro-temporal domain. Self-organizing map artificial neural network (SOM) was applied to clustering of features space. Scale, rate and frequency were used as spatial information of each point and the magnitude component was used as similarity attribute in clustering algorithm. Three mechanisms were considered to select attributes in spectro-temporal features space. Spatial information of clusters, the magnitude component of samples in spectro-temporal domain and the average of the amplitude components of each cluster points were considered as secondary features. The proposed features vectors were used for phonemes classification. The results demonstrate that a significant improvement is obtained in classification rate of different sets of phonemes in comparison to previous clustering-based methods. The obtained results of new features indicate the system error is compensated in all vowels and consonants subsets in compare to weighted K-means clustering.

Keywords:

Paper COI Code

This Paper COI Code is JR_IJE-34-2_017. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1185398/

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Esfandian, N. and Hosseinpour, K.,1400,A Clustering-Based Approach for Features Extraction in Spectro-Temporal Domain Using Artificial Neural Network,https://civilica.com/doc/1185398

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  • 2.     Patil, K., and Elhilali, M., "Biomimetic spectro-temporal features for ...
  • 3.     Mesgarani, N., Slaney, M., and Shamma, S. A., "Discrimination ...
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  • 9.     Ruggles, D. R., Tausend, A. N., Shamma, S. A., ...
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  • 11.   Yen, F. Z., Huang, M. C., and Chi, T.-S., ...
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