Semi-Continuous Hidden Markov Model Optimized Pronunciation Pattern Recognition in English Education

Isolated English Language Digit Recognition Using Hidden Markov Model Toolkit

The main purpose of the study was to develop a speech recognition system for isolated digits of English language using HTK. Speech, in addition to being a tool of communication, is also a symbol of identity and authorization. Two different corpora were collected of audio recordings of isolated digits of English language speakers, in which speakers read numeric digits. Both of the collected corp...

Realization of Hidden Markov Model for English Digit Recognition

The objective of the work described here is to compare the isolated English language digit speech recognition using Hidden Markov Model for speaker independent system. Two different datasets were collected of audio recordings for the said comparison of isolated digits of English language. Speakers here read numeric digits 0 to 9 i.e. ZERO to NINE. One corpus is self recorded signals and other i...

Recurrent Hidden Semi-markov Model

Segmentation and labeling of high dimensional time series data has wide applications in behavior understanding and medical diagnosis. Due to the difficulty of obtaining a large amount the label information, realizing this objective in an unsupervised way is highly desirable. Hidden Semi-Markov Model (HSMM) is a classical tool for this problem. However, existing HSMM and its variants typically m...

Continuous Gesture Recognition Based on Hidden Markov Model

Continuous Density Hidden Markov Model for Hindi Speech Recognition

State of the art automatic speech recognition system uses Mel frequency cepstral coefficients as feature extractor along with Gaussian mixture model for acoustic modeling but there is no standard value to assign number of mixture component in speech recognition process.Current choice of mixture component is arbitrary with little justification. Also the standard set for European languages can no...