Phase reconstruction of spectrograms with linear unwrapping: application to audio signal restoration
This addresses phase reconstruction in audio signal processing, offering incremental improvements for applications like audio restoration.
The paper tackles the problem of reconstructing phase from modified spectrograms for audio signals by analyzing sinusoid mixtures and impulse models to ensure coherence across time and frequency, demonstrating better performance than traditional consistency-based approaches in audio restoration.
This paper introduces a novel technique for reconstructing the phase of modified spectrograms of audio signals. From the analysis of mixtures of sinusoids we obtain relationships between phases of successive time frames in the Time-Frequency (TF) domain. To obtain similar relationships over frequencies, in particular within onset frames, we study an impulse model. Instantaneous frequencies and attack times are estimated locally to encompass the class of non-stationary signals such as vibratos. These techniques ensure both the vertical coherence of partials (over frequencies) and the horizontal coherence (over time). The method is tested on a variety of data and demonstrates better performance than traditional consistency-based approaches. We also introduce an audio restoration framework and observe that our technique outperforms traditional methods.