Physiologically Motivated Feature Extraction for Robust Automatic Speech Recognition
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 4
Abstract
In this paper, a new method is presented to extract robust speech features in the presence of the external noise. The proposed method based on two-dimensional Gabor filters takes in account the spectro-temporal modulation frequencies and also limits the redundancy on the feature level. The performance of the proposed feature extraction method was evaluated on isolated speech words which are extracted from TIMIT corpus and corrupted by background noise. The evaluation results demonstrate that the proposed feature extraction method outperforms the classic methods such as Perceptual Linear Prediction, Linear Predictive Coding, Linear Prediction Cepstral coefficients and Mel Frequency Cepstral Coefficients.
Authors and Affiliations
Ibrahim Missaoui, Zied Lachiri
Keywords
Related Articles
- EP ID EP117836
- DOI 10.14569/IJACSA.2016.070438
- Views 106
- Downloads 0
Identifying and Extracting Named Entities from Wikipedia Database Using Entity Infoboxes
An approach for named entity classification based on Wikipedia article infoboxes is described in this paper. It identifies the three fundamental named entity types, namely; Person, Location and Organization. An entity cl...
High Precision DCT CORDIC Architectures for Maximum PSNR
This paper proposes two optimal Cordic Loeffler based DCT (Discrete Cosine Transform algorithm) architectures: a fast and low Power DCT architecture and a high PSNR DCT architecture. The rotation parameters of CORDIC ang...
NoSQL Racket: A Testing Tool for Detecting NoSQL Injection Attacks in Web Applications
A NoSQL injection attack targets interactive Web applications that employ NoSQL database services. These applications accept user inputs and use them to form query statements at runtime. During NoSQL injection attack, an...
A Better Comparison Summary of Credit Scoring Classification
The credit scoring aim is to classify the customer credit as defaulter or non-defaulter. The credit risk analysis is more effective with further boosting and smoothing of the parameters of models. The objective of this p...
Sensitivity Analysis of Fourier Transformation Spectrometer: FTS Against Observation Noise on Retrievals of Carbon Dioxide and Methane
Sensitivity analysis of Fourier Transformation Spectrometer: FTS against observation noise on retrievals of carbon dioxide and methane is conducted. Through experiments with real observed data and additive noise, it is f...