Results 171 to 180 of about 8,304 (223)
Classification of speech dysfluencies with MFCC and LPCC features [PDF]
Expert Systems With Applications, 2012 The goal of this paper is to discuss comparison of speech parameterization methods: Mel-Frequency Cepstrum Coefficients (MFCC) and Linear Prediction Cepstrum Coefficients (LPCC) for recognizing the stuttered events. Speech samples from UCLASS are used for our analysis. The stuttered events are identified through manual segmentation and used for feature
M Hariharan, Sazali Yaacob
exaly +3 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
Chip design of MFCC extraction for speech recognition
The Integration VLSI Journal, 2002Summary: The Mel Frequency Cepstral Coefficient (MFCC) is one of the most important features required among various kinds of speech applications. In this paper, the first chip for speech features extraction based on MFCC algorithm is proposed. The chip is implemented as an intellectual property, which is suitable to be adopted in a speech recognition ...
Jia-Ching Wang +2 more
exaly +2 more sources
Predicting Formant Frequencies from MFCC Vectors
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006 This work proposes a novel method of predicting formant frequencies from a stream of mel-frequency cepstral coefficients (MFCC) feature vectors. Prediction is based on modelling the joint density of MFCCs and formant frequencies using a Gaussian mixture ...
Jonathan Darch +4 more
openaire +2 more sources
Algorithm of Abnormal Audio Recognition Based on Improved MFCC
Procedia Engineering, 2012 Characteristics extraction has a great effect on the audio training and recognition in the audio recognition system. MFCC algorithm is a typical characteristics extraction method with stable performance and high recognition rate.
Chuan Xie, Xiaoli Cao
exaly +2 more sources
Emotion Detection Using MFCC and Cepstrum Features
Procedia Computer Science, 2015 A tremendous research is being done on Speech Emotion Recognition (SER) in the recent years with its main motto to improve human machine interaction. In this work, the effect of cepstral coefficients in the detection of emotions is performed.
S Lalitha, R Narayanan
exaly +2 more sources
Comparison of different implementations of MFCC
Journal of Computer Science and Technology, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thomas Fang Zheng +2 more
openaire +1 more source