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.
environmental sound recognition non-speech sound recognition audio signal processing acoustic signal processing joint time-frequency feature extraction