Speech Recognition Using Hidden Markov Models

Course Project for Automatic Speech Recognition - EEL 6586
Instructor: Dr. John G Harris

Project Description:
 
The aim of the project was to develop a Limited Vocabulary Isolated Word Recognition System adopting the Hidden Markov Model to statistically model the words in the dictionary. For the project an Irish database containing 10 numerals from zero-nine, spoken by 10 different speakers was used. So, this speech recognition system is speaker dependent.
The project involved the following modules
  Feature Extraction Vector Quantization HMM Training or Building the HMMs Recognition
 



Results:

Overall, there were 100 samples of speech ( 10 words x 10 speakers ). Out of this, 90 were used for training and 10 were used for testing.
On the training set, 100% recognition was achieved. On the test set, the recognition made 2 mistakes. So, on the whole the performance of the recognizer was good. However, the performance of the system can be improved if we have more training samples.



References:
Books:


 MATLAB CODE:

All the MATLAB Code, Codebook vectors, HMMs can be downloaded here

 Download ZIP File


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