this paper introduces a new method of extracting MFCC for speech recognition and it is compared with the conventional MFCC method. The new algorithm reduces the calculation steps by 53% compared to conventional method. Simulation result indicates the new method has a recognition accuracy of 92.93% only 1.5% less than the conventional MFCC method which is has accuracy of 94.43%. However, the num...

A new feature set for ASR called Rate-Spectrum(RS) is proposed. RS is a spectral representation obtained using a computational auditory model. The feature is noise-robust and considerably speaker invariant. RS matches the smoothed log spectrum both in shape and dynamic range variation. DCT is used to reduce dimensionality. Comparison of the proposed features with MFCC is done using an Isolated ...

Existing standard speech coders can provide speech communication of high quality while they degrade the performance of speech recognition systems that use the reconstructed speech by the coders. The main cause of the degradation is that the spectral envelope parameters in speech coding are optimized to speech quality rather than to the performance of speech recognition. For example, mel-frequen...

Mel Frequency Ceptral Coefficient is a very common and efficient technique for signal processing. This paper presents a new purpose of working with MFCC by using it for Hand gesture recognition. The objective of using MFCC for hand gesture recognition is to explore the utility of the MFCC for image processing. Till now it has been used in speech recognition, for speaker identification. The pres...

Background: The mel-frequency cepstral coefficients (MFCC) are relied for their capability to identify pathological speech. The literature suggests that triangular mel-filters that are used in the MFCC calculation provide an approximation of the human auditory perception. This approximation allows quantifying the clinician’s perception of the intelligibility of the patient’s speech that allows ...

A person's voice contains various parameters that convey information such as emotion, gender, attitude, health and identity. This report talks about speaker recognition which deals with the subject of identifying a person based on their unique voiceprint present in their speech data. Pre-processing of the speech signal is performed before voice feature extraction. This process ensures the voice...

Two methods of spectral analysis for noisy speech recognition are proposed and tested in a speaker independent word recognition experiment under an additive white Gaussian noise environment. One is Mel-frequency cepstral coefficients (MFCC) spectral analysis on the autocorrelation sequence of the speech signal and the other is MFCC spectral analysis on its double autocorrelation sequence. The w...

The main bearing is the core component of gas-fired generator, and its reliability directly affects stability whole system. Therefore, it great significance to study fault diagnosis generator. In based on vibration signal, how extract signature features effectively key achieving accurate diagnosis. Based extracting faults, classify efficiently another this, we propose a method Mel frequency cep...