Real-time Soundprism

Muñoz-Montoro, Antonio J.; Ranilla, José; Combarro, Elías F.; Alonso‐Jordá, Pedro

doi:10.1007/s11227-018-2703-0

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…This fact makes real-time performance less accurate than offline performance. In this context, many recent efforts in the field have been focused on improving the robustness and speed of music real-time systems, making them appropriate for mobile devices and for a wide range of real-life contexts [2,1,28].…”

Section: Introductionmentioning

confidence: 99%

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Parallel multichannel music source separation system

et al. 2020

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This paper presents a parallel low latency multichannel source separation system designed to recover the original signals of the instruments that compound a multichannel music recording. Our approach is suitable for many applications based on interactive live broadcast classical music, where a latency of a few seconds can be assumed by online users. The obtained results show that it is possible to reach real-time in the tested scenarios assuming a low latency and combining multi-core architectures with parallel and high performance techniques.

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Section: Introductionmentioning

confidence: 99%

“…In this work, significant improvements have been carried out that clearly differentiate it from our previous work [28]. First, note that ReMAS, which was optimized for low-power processors such as ARM processors, applies the alignment process frame-by-frame.…”

Section: Introductionmentioning

confidence: 99%

Parallel multichannel music source separation system

et al. 2020

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An efficient parallel kernel based on Cholesky decomposition to accelerate Multichannel Non-Negative Matrix Factorization

Muñoz-Montoro

Carabias-Orti

Salvati

et al. 2022

Preprint

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Multichannel Source Separation has been a popular topic, and recently proposed methods based on the local Gaussian model (LGM) have provided promising result despite its high computational cost when several sensors are used. The main reason being due to inversion of a spatial covariance matrix, with a complexity of \(O(I^3)\), being \(I\) the number of sensors. This drawback limits the practical application of this approach for tasks such as sound field reconstruction or virtual reality, among others. In this paper, we present a numerical approach to reduce the complexity of the Multichannel NMF to address the task of audio source separation for scenarios with a high number of sensors such as High Order Ambisonics (HOA) encoding. In particular, we propose a parallel multi-architecture driver to compute the multiplicative update rules in MNMF approaches. The proposed driver has been designed to work on both sequential and multi-core computers, as well as Graphics Processing Units (GPUs) and Intel Xeon coprocessors. The proposed software was written in C language and can be called from numerical computing environments. The proposed solution tries to reduce the computational cost of the multiplicative update rules by using the Cholesky decomposition and by solving several triangular equation systems.The proposal has been evaluated for different scenarios with promising results in terms of execution times for both CPU and GPU. To the best of our knowledge, our proposal is the first system that addresses the problem of reducing the computational cost of full-rank MNMF-based systems using parallel and high performance techniques.

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Real-time Soundprism

Cited by 2 publications

References 21 publications

Parallel multichannel music source separation system

Parallel multichannel music source separation system

An efficient parallel kernel based on Cholesky decomposition to accelerate Multichannel Non-Negative Matrix Factorization

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