Abstract
In the present study, a new feature extraction method based on relative spectra and gammachirp auditory filterbank is proposed for robust noisy speech recognition. The relative spectra filtering are applied to the log of the output of the gammachirp filterbank which incorporates the properties of the cochlear filter in order to remove uncorrelated additive noise components. The performances of this method have been evaluated on the isolated speech word corrupted by real-world noisy environments using the continuous Gausian-Mixture density Hidden Markov Model. The evaluation of the experimental results shows that the proposed method achieves best recognition rates compared to the conventional techniques like Perceptual Linear Prediction (PLP), Linear Predictive Cepstral Coefficients (LPCC) and Mel-Frequency Cepstral Coefficients (MFCC).
Highlights
In many practical applications, the performance of Automatic Speech Recognition (ASR) system is limited due to its lack of the robustness in the presence of background noises
Proposed feature extractor: The proposed feature extraction method is based on relative spectra and gammachirp auditory filterbank for robust noisy speech recognition
The all isolated-words used in the testing phase were corrupted by different background noise (Passing-car, Shopping-mall, Rain, Sea waves noise) for various SNR ranging from -3 to 9 dB
Summary
The performance of Automatic Speech Recognition (ASR) system is limited due to its lack of the robustness in the presence of background noises. To increase the robustness of ASR-systems, the speech feature must be less sensitive in the presence of background noises, while retaining good of distinguished properties (Gajic and Paliwal, 2006). The auditory system of human has a remarkable ability to recognize the speech signal in noisy environments This ability has inspired the development of many feature extraction algorithms which take into account certain knowledge on human speech perception (Gajic and Paliwal, 2006). A new auditory filter known as gammachirp filter is developed by Irino and Patterson (1997, 2006) This filter with an asymmetric amplitude spectrum represents a good approximation to the asymmetry and level dependent characteristics of the cochlea filtering (Meddis et al, 2010)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Research Journal of Applied Sciences, Engineering and Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
