Abstract
A novel method for audio time stretching has been developed. In time stretching, the audio signal’s duration is expanded, whereas its frequency content remains unchanged. The proposed time stretching method employs the new concept of fuzzy classification of time-frequency points, or bins, in the spectrogram of the signal. Each time-frequency bin is assigned, using a continuous membership function, to three signal classes: tonalness, noisiness, and transientness. The method does not require the signal to be explicitly decomposed into different components, but instead, the computing of phase propagation, which is required for time stretching, is handled differently in each time-frequency point according to the fuzzy membership values. The new method is compared with three previous time-stretching methods by means of a listening test. The test results show that the proposed method yields slightly better sound quality for large stretching factors as compared to a state-of-the-art algorithm, and practically the same quality as a commercial algorithm. The sound quality of all tested methods is dependent on the audio signal type. According to this study, the proposed method performs well on music signals consisting of mixed tonal, noisy, and transient components, such as singing, techno music, and a jazz recording containing vocals. It performs less well on music containing only noisy and transient sounds, such as a drum solo. The proposed method is applicable to the high-quality time stretching of a wide variety of music signals.
Highlights
Time-scale modification (TSM) refers to an audio processing technique, which changes the duration of a signal without changing the frequencies contained in that signal [1,2,3]
The transients are processed so that the transient energy is mostly contained on a single synthesis frame, effectively suppressing the transient smearing artifact, which is typical for the phase vocoder based TSM
The listening test results presented in this paper suggest that the proposed method performs generally better than a state-of-the-art algorithm and is competitive with commercial software
Summary
Time-scale modification (TSM) refers to an audio processing technique, which changes the duration of a signal without changing the frequencies contained in that signal [1,2,3]. A standard solution for reducing transient smearing is to apply a phase reset or phase locking at detected transient locations of the input signal [23,24,25] As another approach to overcome these problems in the phase vocoder, TSM techniques using classification of spectral components based on their signal type have been proposed recently. Using the information from the peak classification, the phase modification applied in the technique is based only on the sinusoidally classified peaks It uses the method of [23] to detect and preserve transient components. A standard overlap-add scheme with a shorter analysis window is used for the transient components Both of the above methods are based on a binary classification of the spectral bins.
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