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The performance of any speech based systems depends on the quality of input speech signals. The signal to noise ratio (SNR) is considered to be a measure of the quality of speech signal. This paper reports some analyses (based on experimental evaluations) that are focused on calculating the quality of the speech signal so as to improve the overall accuracy of the system. As compared to existing methods...
This paper presents a study on the varying degree of speaker identity information that is embedded across the MFCCs feature. A DTW based template matching model has been used on a set of 100 speakers' data, each from the CSLU speaker recognition database and the NITs text-dependent speaker verification database. The 39 dimensional MFCC feature vector, conventionally used in the automatic speaker recognition...
In this paper, we analyse the effect of frame size and frame shift in detection of vowel on set point (VOP) under clean and noisy conditions, towards making VOP detection more accurate in practical scenario. For detection of VOP we use the state of art technique which combines the complementary evidences from excitation source, spectral peaks, and modulation spectrum. We carry out our experiments...
Statistical pattern recognition has been considered to be one of the most successful approaches in the recent advancement of speech and speaker recognition. Out of all the approaches Hidden Markov Models, Gaussian mixture models and Vector Quantization has been considered to be one of the most successful techniques in regards to the performance of the speaker recognition systems. However the performance...
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