Speech Recognition System Base on Linear Predictive Coding (LPC) and Hidden Markov Model (HMM) Using Matlab for Speaker Identification

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Speech Recognition System Base on Linear Predictive Coding (LPC) and Hidden Markov Model (HMM) Using Matlab for Speaker Identification

System Speech Recognition is a recognition process using MatLab that can identify a person with voice processing. The basic purpose of the study was to identify and classify the utterances of different people. Identification to know who is saying these words is by matching the characteristics of speech in the database with the input utterance. Characteristics of speech can be distinguished by extraction with a coding technique, a fundamental frequency (pitch), formant and energy. Coding techniques commonly used by the National Institute of Standards Technology (NIST) in the lawyer-ekstraksian speech signal is LPC (Linier Predictiv Coding). Unique identity of each person can be identified using a statistical model of hidden Markov model (HMM).

Statement of Responsibility

Author(s)

Andriana - Personal Name
Zurkarnain - Personal Name
Barmawi - Personal Name

Edition

Call Number

Subject(s)

Speaker Recognition

Classification

600

Series Title

GMD

Text

Language

English

Publisher

Prosiding Engineering International Conference 2013

Publishing Year

2013

Publishing Place

Universitas Negeri Semarang

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APA Citation

Andriana. (2013).Speech Recognition System Base on Linear Predictive Coding (LPC) and Hidden Markov Model (HMM) Using Matlab for Speaker Identification.(Electronic Thesis or Dissertation). Retrieved from https://localhost/etd