Results 191 to 200 of about 8,304 (223)

MFCC and SVM Based Recognition of Chinese Vowels

2005
The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no efficient method to solve it yet. In this paper, we propose a new approach to the recognition of Chinese vowels via the support vector machine (SVM) with the Mel-Frequency Cepstral ...
Fuhai Li 0001, Jinwen Ma, Dezhi Huang
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Noise robust speaker identification by dividing MFCC

2014 6th International Symposium on Communications, Control and Signal Processing (ISCCSP), 2014
Until now, systems using speaker identification have not been widely used. The main reason is because the identification accuracy is low. Therefore, in this paper, we report the results of modulation frequency analysis and propose a novel method using effectively modulation frequency components of vocal tract characteristics.
Kizuki Matsumoto, Noboru Hayasaka, Youji Iiguni   +2 more
openaire   +1 more source

An efficient MFCC extraction method in speech recognition

2006 IEEE International Symposium on Circuits and Systems, 2006
This paper introduces a new algorithm of extracting MFCC for speech recognition. The new algorithm reduces the computation power by 53% compared to the conventional algorithm. Simulation results indicate the new algorithm has a recognition accuracy of 92.93%.
Wei Han, Cheong-Fat Chan, Oliver Chiu-sing Choy, Kong-Pang Pun   +3 more
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An Alternative to MFCCs for ASR

Interspeech 2020, 2020
Pegah Ghahramani, Hossein Hadian, Daniel Povey, Hynek Hermansky, Sanjeev Khudanpur   +4 more
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Study on Fractal Dimension modified MFCC

Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering, 2022
Mi Pan, Li Wang
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Speech recognition using MFCC and DTW

2014 International Conference on Advances in Electrical Engineering (ICAEE), 2014
Speech recognition has wide range of applications in security systems, healthcare, telephony military, and equipment designed for handicapped. Speech is continuous varying signal. So, proper digital processing algorithm has to be selected for automatic speech recognition system. To obtain required information from the speech sample, features have to be
null Bhadragiri Jagan Mohan, null Ramesh Babu N.   +1 more
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Speech Recognition Combining MFCCs and Image Features

2016
Automatic speech recognition (ASR) task constitutes a well-known issue among fields like Natural Language Processing (NLP), Digital Signal Processing (DSP) and Machine Learning (ML). In this work, a robust supervised classification model is presented (MFCCs + autocor + SVM) for feature extraction of solo speech signals.
Stamatis Karlos, Nikos Fazakis, Katerina Karanikola, Sotiris B. Kotsiantis, Kyriakos N. Sgarbas   +4 more
openaire   +1 more source

MFCCs and TEO-MFCCs for Stress Detection on Women Gender through Deep Learning Analysis

2023 9th International Conference on Computer and Communication Engineering (ICCCE), 2023
Nur Aishah Zainal, Ani Liza Asnawi, Ahmad Zamani Jusoh, Siti Noorjannah Ibrahim, Huda Adibah Mohd Ramli, Nor Fadhillah Mohamed Azmin   +5 more
openaire   +1 more source

Speech and Language Recognition using MFCC and DELTA-MFCC

International Journal of Engineering Trends and Technology, 2014
Samiksha Sharma, Anupam Shukla, Pankaj Mishra   +2 more
openaire   +1 more source

Integrating the energy information into MFCC

6th International Conference on Spoken Language Processing (ICSLP 2000), 2000
Fang Zheng 0001, Guoliang Zhang
openaire   +1 more source