Results 171 to 180 of about 10,198 (208)

Auditory model based modified MFCC features

2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010
Using spectral and spectro-temporal auditory models, we develop a computationally simple feature vector based on the design architecture of existing mel frequency cepstral coefficients (MFCCs). Along with the use of an optimized static function to compress a set of filter bank energies, we propose to use a memory-based adaptive compression function to ...
Saikat Chatterjee, W. Bastiaan Kleijn
openaire   +2 more sources

Significance of chirp MFCC as a feature in speech and audio applications

Computer Speech and Language
A novel feature, based on the chirp z-transform, that offers an improved representation of the underlying true spectrum is proposed. This feature, the chirp MFCC, is derived by computing the Mel frequency cepstral coefficients from the chirp magnitude spectrum, instead of the Fourier transform magnitude spectrum.
Johanan Joysingh S, P Vijayalakshmi
exaly   +4 more sources

Classification of Heart Sounds Using MFCC and CNN

2021
An excellent heart sound classification system can be used as a good method to complete the daily heart sound detection under the condition of low cost and high efficiency, which is convenient to detect problems in the early stage of heart disease, and at the same time can alleviate the problem of medical staff shortage.
Kai Wang, Kang Chen
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +2 more sources

Optimizing MFCC parameters for the automatic detection of respiratory diseases

Applied Acoustics
Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) is widely used for automatic analysis, with MFCC extraction commonly relying on default parameters.
Visara Urovi, Yuyang Yan
exaly   +5 more sources

Speaker recognition by combining MFCC and phase information

Interspeech 2007, 2007
In conventional speaker recognition method based on MFCC, the phase information has been ignored. In this paper, we proposed a method that integrates the phase information on a speaker recognition method. The speaker identification experiments were performed using NTT database which consists of sentences uttered at normal speed mode by 35 Japanese ...
Seiichi Nakagawa, Kouhei Asakawa, Longbiao Wang   +2 more
openaire   +2 more sources

An Alternative to MFCCs for ASR

Interspeech 2020, 2020
Pegah Ghahramani, Hossein Hadian, Daniel Povey, Hynek Hermansky, Sanjeev Khudanpur   +4 more
openaire   +1 more source

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
openaire   +2 more sources