Digital Signal Processing

Yogesh S. Angal ¹, Pawan K. Ajmera ², Raghunath S. Holambe ³, Rajan H. Chile ⁴

Affiliations
1 Department of Instrumentation Engineering, Padmashree Dr.D.Y. Patil Institute of Engineering and Technology, Pimpri, Pune-18, Maharashtra, IN
2 S.G.G.S. Institute of Engineering and Technolgy, Nanded. Maharashtra State (M.S.), IN
3 Department of Instrumentation Engineering at S.G.G.S. Institute of Engineering and Technology, Nanded Maharashtra State (M.S.), IN
4 Department of Instrumentation Engineering at S.G.G.S. Institute of Engineering and Technology, Nanded Maharashtra State (M.S.) 431 607, IN

Abstract

This paper presents a new feature extraction technique for speech recognition using Radon Transform (RT) and Discrete Cosine Transform (DCT). A spectrogram is a time varying spectrum(forming an image) that shows how the spectral density of a signal varies with time. In the proposed scheme speech specific features have been extracted by applying image processing technique to the patterns available in the spectrogram. Radon transform has been used to derive the effective acoustic features from speech spectrogram. The proposed technique computes radon projections for nine orientations and captures the acoustic characteristics of the speech spectrogram. DCT applied on Radon projections yields low dimensional feature vectors. The technique is computationally efficient, speaker-independent, robust to session variations and insensitive to additive noise. Radon projections for seven orientations capture the acoustic characteristics of the spectrogram. The performance of the proposed algorithm has been evaluated in presence of additive white Gaussian noise from (30dB to -5dB SNR) on Texas Instruments-46(TI-46) speech database. The performance of the proposed technique in noisy environment is much better than existing popular algorithms.

Keywords

Speech Recognition, Spectrogram, Feature Extraction, Radon Transform, Discrete Cosine Transform.

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