Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech

Computer Science – Multimedia

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

4 pages

Scientific paper

In this paper, we discuss the issues in automatic recognition of vowels in Persian language. The present work focuses on new statistical method of recognition of vowels as a basic unit of syllables. First we describe a vowel detection system then briefly discuss how the detected vowels can feed to recognition unit. According to pattern recognition, Support Vector Machines (SVM) as a discriminative classifier and Gaussian mixture model (GMM) as a generative model classifier are two most popular techniques. Current state-ofthe- art systems try to combine them together for achieving more power of classification and improving the performance of the recognition systems. The main idea of the study is to combine probabilistic SVM and traditional GMM pattern classification with some characteristic of speech like band-pass energy to achieve better classification rate. This idea has been analytically formulated and tested on a FarsDat based vowel recognition system. The results show inconceivable increases in recognition accuracy. The tests have been carried out by various proposed vowel recognition algorithms and the results have been compared.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-610428

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.