Reverberation features identification from music recordings using the discrete wavelet transform

This paper presents a method of extracting reverberation features from music recordings. First, we perform a short time Fourier transform to transform the audio signal into a 2D time-frequency representation in which reverberation features appear as blurring of spectral features in the time dimension. Employing image analysis method we may quantitatively estimate the amount of reverberation by transforming the STFT “image” to a wavelet domain where we can perform efficient edge detection and characterization. Experiments demonstrate that quantitative estimates of reverberation time extracted in this way are strongly correlated with physical measurements.