This paper describes the principle of MFCC feature extraction and the knowledge of human auditory masking effect in order to introduce a modified-MFCC feature extraction that can improve the robustness of speech recognition systems.

Performance of an automatic speech recognition (ASR) system tends to be dramatically degraded in the presence of impulsive noise. In the previous work [1], we proposed flooring the observation probability (FOP) to compensate the adverse effect of impulsive noise on sensitive dimensions of Mel-frequency cepstral coefficient (MFCC) features. Linear prediction cepstral coefficient (LPCC) is anothe...

Vocal and nonvocal segmentation is an important task in singing voice signal processing. Before identifying the singer it is necessary to locate the singer’s voice in a song. Maximum of the songs start with a piece of instrumental accompaniment known as ‘prelude’ in musical terms after which the singing voice comes into play. Therefore, it is necessary to detect the vocal region in the song in ...

In this paper, a novel pitch mean based frequency warping (PMFW) method is proposed to reduce the pitch variability in speech signals at the frontend of speech recognition. The warp factors used in this process are calculated based on the average pitch of a speech segment. Two functions to describe the relations between the frequency warping factor and the pitch mean are defined and compared. W...

This paper deals with LP based Mel-Generalized cepstrum which has been used as front-end for Hidden Markov Model (HMM) based speech recognition and it incorporates equal-loudness power law as well as auditory-like frequency resolution. To utilize the generalized cepstral representation, the model spectrum can be varied continuously from the all-pole spectrum to that represented by the cepstrum ...

In this paper, we define an F0 quantization scheme for a very low bit rate speech coder based on HMM (Hidden Markov Model). In the coding system, the encoder carries out phoneme recognition, and transmits phoneme indices, state durations and F0 information to the decoder. In the decoder, phoneme HMMs are concatenated according to the phoneme indices, and a sequence of mel-cepstral coefficient v...

Speech emotion recognition is one of the latest challenges in speech processing and Human Computer Interaction (HCI) in order to address the operational needs in real world applications. Besides human facial expressions, speech has proven to be one of the most promising modalities for automatic human emotion recognition. Speech is a spontaneous medium of perceiving emotions which provides in-de...

Development of robust and efficient front-end is crucial for robust ASR. Proper time and frequency resolution of the TFR of speech, motivated by the auditory models is considered an important factor for robustness. An efficient method of realizing a variable resolution TFR using DTFT/Goertzel algorithm is proposed instead of the standard FFT based approach. It is shown that the new representati...