Speech Recognition in a Multi-speaker Environment by Using Hidden Markov Model and Mel-frequency Approach

The sound is a useful and versatile form of communication, where each sound have characteristics and levels of different frequency. Sound serves two basic functions for people around the world: signaling and communication. Several problems are found in sounds identifying, like pitch, velocity, and a...

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Bibliographic Details
Published in2016 Third International Conference on Computing Measurement Control and Sensor Network (CMCSN) pp. 80 - 83
Main Authors Watada, Junzo, Hanayuki
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.05.2016
Subjects
Emotion recognition
Feature extraction
Hidden Markov Model
Hidden Markov models
Human voice
Mel frequency cepstral coefficient
Mel-frequency
Multi-speaker Environment
Speech
Speech recognition
Online AccessGet full text
DOI10.1109/CMCSN.2016.47

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Summary:The sound is a useful and versatile form of communication, where each sound have characteristics and levels of different frequency. Sound serves two basic functions for people around the world: signaling and communication. Several problems are found in sounds identifying, like pitch, velocity, and accuracy of processing voice data. The motivation of this research is to recognize and analyze human voice in a multi-speaker environment from the meeting or indirect conversation. In this research, a Hidden Markov Model approach is proposed as an emotion classifier to carry out testing phases using speech data.
DOI:10.1109/CMCSN.2016.47