Download Comb-filter free audio mixing using STFT magnitude spectra and phase estimation This paper presents a new audio mixing algorithm which avoids comb-filter distortions when mixing an input signal with timedelayed versions of itself. Instead of a simple signal addition in the time domain, the proposed method calculates the short-time Fourier magnitude spectra of the input signals and adds them. The sum determines the output magnitude on the time-frequency plane, whereas a modified RTISI algorithm estimates the missing phase information. An evaluation using PEAQ shows that the proposed method yields much better results than temporal mixing for nonzero delays up to 10 ms.
Download Source-Filter based Clustering for Monaural Blind Source Separation In monaural blind audio source separation scenarios, a signal mixture is usually separated into more signals than active sources. Therefore it is necessary to group the separated signals to the final source estimations. Traditionally grouping methods are supervised and thus need a learning step on appropriate training data. In contrast, we discuss unsupervised clustering of the separated channels by Mel frequency cepstrum coefficients (MFCC). We show that replacing the decorrelation step of the MFCC by the non-negative matrix factorization improves the separation quality significantly. The algorithms have been evaluated on a large test set consisting of melodies played with different instruments, vocals, speech, and noise.
Download Improving RTISI Phase Estimation with Energy Order and Phase Unwrapping This paper presents two ways to improve the Real-Time Iterative Spectrogram Inversion (RTISI) algorithm. The standard RTISI phase estimator with look-ahead processes the buffered frames in reverse order. We show that better results are achieved by controlling this order according to frame energy. Another improvement is to initialize the last row of the phase estimator buffer by progressing the unwrapped phase difference of the previous frames. Furthermore, we extend these improvements to dual window length phase estimation and analyze the performance in SER with respect to different analysis window lengths.
Download Multiresolution STFT Phase Estimation with Frame-Wise Posterior Window-Length Decision This paper presents an extension to the dual-window-length Real-Time Iterative Spectrogram Inversion phase estimation algorithm (RTISI). Instead of a transient detection in advance, the phase estimator itself determines the correct window length when the phase information for all window lengths have already been estimated. This way, we get significant improvements compared with the previous method. Additionally, we extend this estimator to configurations with three or more window lengths.