Emilia Gómez

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We present a novel system for the automatic extraction of the main melody from polyphonic music recordings. Our approach is based on the creation and characterization of pitch contours, time continuous sequences of pitch candidates grouped using auditory streaming cues. We define a set of contour characteristics and show that by studying their distributions(More)
We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the music information retrieval (MIR) community along in the past, as it provides a(More)
In this paper we propose a text represention for musical chord symbols that is simple and intuitive for musically trained individuals to write and understand, yet highly structured and unambiguous to parse with computer programs. When designing feature extraction algorithms, it is important to have a hand annotated test set providing a ground truth to(More)
Although the process of analyzing an audio recording of a music performance is complex and difficult even for a human listener, there are limited forms of information that may be tractably extracted and yet still enable interesting applications. We discuss melody-roughly, the part a listener might whistle or hum-as one such reduced descriptor of music(More)
A cover version1 is an alternative rendition of a previously recorded song. Given that a cover may differ from the original song in timbre, tempo, structure, key, arrangement, or language of the vocals, automatically identifying cover songs in a given music collection is a rather difficult task. The music information retrieval (MIR) community has paid much(More)
We present Essentia 2.0, an open-source C++ library for audio analysis and audio-based music information retrieval released under the Affero GPL license. It contains an extensive collection of reusable algorithms which implement audio input/output functionality, standard digital signal processing blocks, statistical characterization of data, and a large set(More)
be achieved by Machine Learning. • Necessity to consider structural description for key: combine with rhythmic and structural description. System block diagram In this paper, we evaluate two approaches for key estimation from polyphonic audio recordings. Our goal is to compare between a strategy using a cognition-inspired model and several machine learning(More)
This paper deals with automatic transcription of flamenco music recordings, more specifically a cappella singing. We first study the specificities of flamenco singing and propose a transcription system based on fundamental frequency and energy estimation, which incorporates an iterative strategy for note segmentation and labelling. The proposed approach is(More)
We provide a survey of the field of Music Information Retrieval (MIR), in particular paying attention to latest developments, such as semantic auto-tagging and user-centric retrieval and recommendation approaches. We first elaborate on well-established and proven methods for feature extraction and music indexing, from both the audio signal and contextual(More)