Marius Miron

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In order to better understand the musical properties which elicit an increased sensation of wanting to move when listening to music-groove-we investigate the effect of adding syncopation to simple piano melodies, under the hypothesis that syncopation is correlated to groove. Across two experiments we examine listeners' experience of groove to synthesized(More)
The issue of tuning in Indian classical music has been, historically, a matter of theoretical debate. In this paper, we study its contemporary practice in sung performances of Carnatic and Hindustani music following an empiric and quantitative approach. To do so, we select stable fundamental frequencies, estimated via a standard algorithm, and construct(More)
In this paper we introduce a low-latency monaural source separation framework using a Convolutional Neural Network (CNN). We use a CNN to estimate time-frequency soft masks which are applied for source separation. We evaluate the performance of the neural network on a database comprising of musical mixtures of three instruments: voice, drums, bass as well(More)
In this paper we propose an offline method for refining audio-to-score alignment at the note level in the context of orchestral recordings. State-of-the-art score alignment systems estimate note onsets with a low time resolution, and without detecting note offsets. For applications such as score-informed source separation we need a precise alignment at note(More)
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(More)
This paper presents a drum transcription algorithm adjusted to the constraints of real-time audio. We introduce an instance filtering (IF) method using sub-band onset detection, which improves the performance of a system having at its core a feature-based K-nearest neighbor classifier (KNN). The architecture proposed allows for adapting different parts of(More)
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(More)
This paper describes an open-source software for real-time rhythm annotation. The software integrates several modules for graphical user interface, user management across a network, tap recording, audio playing, midi interfacing and threading. It is a powerful tool for conducting listening tests, but can also be used for beat annotation of music or in a(More)
The classical music traditions of the Indian subcontinent, Hindustani and Carnatic, offer an excellent ground on which to test the limitations of current music information research approaches. At the same time, studies based on these music traditions can shed light on how to solve new and complex music modeling problems. Both traditions have very distinct(More)
The thesis aims to develop a system of Hindustani tala automatic recognition which can be trained by building a labeled corpus of Hindustani songs with tabla accompaniment. Most of the research concerning rhythm in the North Indian classical music was developed around monophonic recordings and the scope was just recognizing the tabla strokes or modeling the(More)