Score-Informed Sparseness for Source Separation
نویسندگان
چکیده
Audio source separation is a useful preprocessing step for remixing or transcription of music. It can be shown, that the separation quality increases, if the separation algorithm gets additional side information, e.g. the score of the current mixture [5]. In many cases the score of a musical piece is not available and has to be extracted by a professional musician or an automatic music transcription algorithm. To avoid both necessities, we will propose a source separation algorithm, which utilizes only the temporal activity (TA) of each instrument in the mixture. Compared to the whole score, this TA can be evaluated with much less experience in music transcription. To improve separation quality, the TA controls the sparsity of a non-negative tensor factorization. We will show, that for certain mixtures, this TA is a sufficient information for source separation. If TA is not sufficient, it can be utilized as a preprocessing step for further blind source separation algorithms.
منابع مشابه
Monaural Score-Informed Source Separation for Classical Music Using Convolutional Neural Networks
Score information has been shown to improve music source separation when included into non-negative matrix factorization (NMF) frameworks. Recently, deep learning approaches have outperformed NMF methods in terms of separation quality and processing time, and there is scope to extend them with score information. In this paper, we propose a score-informed separation system for classical music th...
متن کاملEvaluation of a Score-informed Source Separation System
In this work, we investigate a method for score-informed source separation using Probabilistic Latent Component Analysis (PLCA). We present extensive test results that give an indication of the performance of the method, its strengths and weaknesses. For this purpose, we created a test database that has been made available to the public, in order to encourage comparisons with alternative methods.
متن کاملScore-Informed Source Separation for Musical Audio Recordings
In recent years, source separation has been a central research topic in music signal processing, with applications in stereo-to-surround up-mixing, remixing tools for DJs or producers, instrument-wise equalizing, karaoke systems, and pre-processing in music analysis tasks. Musical sound sources, however, are often strongly correlated in time and frequency, and without additional knowledge about...
متن کاملImproving Score-Informed Source Separation for Classical Music through Note Refinement
Signal decomposition methods such as Non-negative Matrix Factorization (NMF) demonstrated to be a suitable approach for music signal processing applications, including sound source separation. To better control this decomposition, NMF has been extended using prior knowledge and parametric models. In fact, using score information considerably improved separation results. Nevertheless, one of the...
متن کاملScore-Informed Source Separation for Multichannel Orchestral Recordings
This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, automatic score alignment methods are reliable when allowing a tolerance window around the actual on...
متن کامل