International Conference on Computer and Knowledge Engineering

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A Genetic-based Fusion Approach of Persian and Universal Phonetic results for Spoken Language Identification

Authors :

Ashkan Moradi¹ Yasser Shekofteh² Saeed Zarei³

1- Computer Science and Engineering Department, Shahid Beheshti University, Tehran, Iran 2- Computer Science and Engineering Department, Shahid Beheshti University, Tehran, Iran 3- Computer Science and Engineering Department, Shahid Beheshti University, Tehran, Iran

Keywords :

Spoken language identification, Phonetic-based approach, perplexity, Classifier fusion, Genetic Algorithm

Abstract :

Automatic Spoken language identification (LID) refers to the automatic process of identifying languages spoken in the audio files. Pure acoustic approaches have shown great potential in LID. Since acoustic approaches have become more and more popular, phonetic information has been largely overlooked. In this paper, we present a fusion approach based on the score probabilities of two phonetic LID systems. There are two SVM classifiers trained on perplexities as their feature vectors which are obtained from phone language models of different phone recognizers. Two phone recognizers are here utilized; one decodes the speech file to a sequence of IPA alphabet, as a universal phone recognizer [1], and the other is a Farsi phone recognizer which is trained on FARSDAT databases. The experimental results conducted on 27 languages within the NIST-LRE09 corpus demonstrated that the proposed fusion approach could greatly increase the classification accuracy of target languages.

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