HMM based isolated Kannada digit recognition system using MFCC

H. Muralikrishna; T. Ananthakrishna; Kumara Shama

doi:10.1109/ICACCI.2013.6637264

HMM based isolated Kannada digit recognition system using MFCC

H. Muralikrishna, T. Ananthakrishna, Kumara Shama

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

In this paper we have implemented Kannada isolated digit recognition system using Mel frequency cepstral coefficients (MFCC) as feature vector. The system is designed to recognize isolated utterances of Kannada numbers. MFCC are used as the features and Hidden Markov Model (HMM) as pattern recognizer. K-means procedure is performed on the feature vectors to obtain the observation sequence. Discrete HMM is used in the system. The system is developed by considering the requirement of a voice controlled machine in Kannada language. Performance of the system is evaluated and compared based on the MFCC along with its first and second order derivatives.

Original language	English
Title of host publication	Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
Pages	730-733
Number of pages	4
DOIs	https://doi.org/10.1109/ICACCI.2013.6637264
Publication status	Published - 2013
Event	2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 - Mysore, India Duration: 22-08-2013 → 25-08-2013

Conference

Conference	2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
Country/Territory	India
City	Mysore
Period	22-08-13 → 25-08-13

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Information Systems

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10.1109/ICACCI.2013.6637264

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title = "HMM based isolated Kannada digit recognition system using MFCC",

abstract = "In this paper we have implemented Kannada isolated digit recognition system using Mel frequency cepstral coefficients (MFCC) as feature vector. The system is designed to recognize isolated utterances of Kannada numbers. MFCC are used as the features and Hidden Markov Model (HMM) as pattern recognizer. K-means procedure is performed on the feature vectors to obtain the observation sequence. Discrete HMM is used in the system. The system is developed by considering the requirement of a voice controlled machine in Kannada language. Performance of the system is evaluated and compared based on the MFCC along with its first and second order derivatives.",

author = "H. Muralikrishna and T. Ananthakrishna and Kumara Shama",

year = "2013",

doi = "10.1109/ICACCI.2013.6637264",

language = "English",

isbn = "9781467362153",

pages = "730--733",

booktitle = "Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013",

note = "2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 ; Conference date: 22-08-2013 Through 25-08-2013",

}

Muralikrishna, H, Ananthakrishna, T & Shama, K 2013, HMM based isolated Kannada digit recognition system using MFCC. in Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013., 6637264, pp. 730-733, 2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013, Mysore, India, 22-08-13. https://doi.org/10.1109/ICACCI.2013.6637264

TY - GEN

T1 - HMM based isolated Kannada digit recognition system using MFCC

AU - Muralikrishna, H.

AU - Ananthakrishna, T.

AU - Shama, Kumara

PY - 2013

Y1 - 2013

N2 - In this paper we have implemented Kannada isolated digit recognition system using Mel frequency cepstral coefficients (MFCC) as feature vector. The system is designed to recognize isolated utterances of Kannada numbers. MFCC are used as the features and Hidden Markov Model (HMM) as pattern recognizer. K-means procedure is performed on the feature vectors to obtain the observation sequence. Discrete HMM is used in the system. The system is developed by considering the requirement of a voice controlled machine in Kannada language. Performance of the system is evaluated and compared based on the MFCC along with its first and second order derivatives.

AB - In this paper we have implemented Kannada isolated digit recognition system using Mel frequency cepstral coefficients (MFCC) as feature vector. The system is designed to recognize isolated utterances of Kannada numbers. MFCC are used as the features and Hidden Markov Model (HMM) as pattern recognizer. K-means procedure is performed on the feature vectors to obtain the observation sequence. Discrete HMM is used in the system. The system is developed by considering the requirement of a voice controlled machine in Kannada language. Performance of the system is evaluated and compared based on the MFCC along with its first and second order derivatives.

UR - http://www.scopus.com/inward/record.url?scp=84891934386&partnerID=8YFLogxK

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U2 - 10.1109/ICACCI.2013.6637264

DO - 10.1109/ICACCI.2013.6637264

M3 - Conference contribution

AN - SCOPUS:84891934386

SN - 9781467362153

SP - 730

EP - 733

BT - Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013

T2 - 2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013

Y2 - 22 August 2013 through 25 August 2013

ER -

HMM based isolated Kannada digit recognition system using MFCC

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