English Language Speech Recognition using MFCC and HMM

被引：0

作者：

Naithani, Kanchan ^{[1
]}

Thakkar, V. M. ^{[1
]}

Semwal, Ashish ^{[2
]}

机构：

[1] Govind Ballabh Pant Inst Engn & Technol, Dept Comp Sci & Engn, Pauri Garhwal, Uttarakhand, India

[2] HNBGU, Dept Comp Sci & Engn, Srinagar, Uttarakhand, India

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN INTELLIGENT AND COMPUTING IN ENGINEERING (RICE III) | 2018年

关键词：

Speech Recognition; Mel-Frequency Cepstral Coefficients (MFCC); Hidden Markov Model (HMM); Spectrogram; Periodogram;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Recognition of speech is a process, which can be outlined as understanding of human speech, processing it into a machine-readable format and utilizing its realization for real time applications. English, the international language, holds the largest vocabulary among the languages, and it is often used for giving commands and for speech recognition in many areas. This paper implements and exploits Mel Frequency Cepstral Coefficient and Hidden Markov Model Techniques to evaluate the competence of speech recognition. This paper displays the Periodogram and Spectrogram of different English commands and commonly used English phrases which are observed after the evaluation of varying pitches for unique English phrases used as commands inserted using the graphical user interface. The result thus obtained displays differences of multiple users speaking commands and commonly used English phrases in multiple accents under unsupervised learning and partially known Hidden Markov Model.

引用

页数：7