Comparison of techniques for environmental sound recognition

This paper presents a comprehensive comparative study of artificial neural networks, learning vector quantization and dynamic time warping classification techniques combined with stationary/non-stationary feature extraction for environmental sound recognition. Results show 70% recognition using mel frequency cepstral coefficients or continuous wavelet transform with dynamic time warping.

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