Download Stationary/transient Audio Separation Using Convolutional Autoencoders
Extraction of stationary and transient components from audio has many potential applications to audio effects for audio content production. In this paper we explore stationary/transient separation using convolutional autoencoders. We propose two novel unsupervised algorithms for individual and and joint separation. We describe our implementation and show examples. Our results show promise for the use of convolutional autoencoders in the extraction of sparse components from audio spectrograms, particularly using monophonic sounds.
Download Time Scale Modification of Audio Using Non-Negative Matrix Factorization
This paper introduces an algorithm for time-scale modification of audio signals based on using non-negative matrix factorization. The activation signals attributed to the detected components are used for identifying sound events. The segmentation of these events is used for detecting and preserving transients. In addition, the algorithm introduces the possibility of preserving the envelopes of overlapping sound events while globally modifying the duration of an audio clip.
Download Audio Morphing Using Matrix Decomposition and Optimal Transport
This paper presents a system for morphing between audio recordings in a continuous parameter space. The proposed approach combines matrix decompositions used for audio source separation with displacement interpolation enabled by 1D optimal transport. By interpolating the spectral components obtained using nonnegative matrix factorization of the source and target signals, the system allows varying the timbre of a sound in real time, while maintaining its temporal structure. Using harmonic / percussive source separation as a pre-processing step, the system affords more detailed control of the interpolation in perceptually meaningful dimensions.
Download Graph-Based Audio Looping and Granulation
In this paper we describe similarity graphs computed from timefrequency analysis as a guide for audio playback, with the aim of extending the content of fixed recordings in creative applications. We explain the creation of the graph from the distance between spectral frames, as well as several features computed from the graph, such as methods for onset detection, beat detection, and cluster analysis. Several playback algorithms can be devised based on conditional pruning of the graph using these methods. We describe examples for looping, granulation, and automatic montage.