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Dive into the research topics where Nicolas Wack is active.

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Featured researches published by Nicolas Wack.


acm multimedia | 2005

Content-based music audio recommendation

Pedro Cano; Markus Koppenberger; Nicolas Wack

We present the MusicSurfer, a metadata free system for the interaction with massive collections of music. MusicSurfer automatically extracts descriptions related to instrumentation, rhythm and harmony from music audio signals. Together with efficient similarity metrics, the descriptions allow navigation of multimillion track music collections in a flexible and efficient way without the need for metadata nor human ratings.


acm multimedia | 2013

ESSENTIA: an open-source library for sound and music analysis

Dmitry Bogdanov; Nicolas Wack; Emilia Gómez; Sankalp Gulati; Perfecto Herrera; Oscar Mayor; Gerard Roma; Justin Salamon; José R. Zapata; Xavier Serra

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 of spectral, temporal, tonal and high-level music descriptors. The library is also wrapped in Python and includes a number of predefined executable extractors for the available music descriptors, which facilitates its use for fast prototyping and allows setting up research experiments very rapidly. Furthermore, it includes a Vamp plugin to be used with Sonic Visualiser for visualization purposes. The library is cross-platform and currently supports Linux, Mac OS X, and Windows systems. Essentia is designed with a focus on the robustness of the provided music descriptors and is optimized in terms of the computational cost of the algorithms. The provided functionality, specifically the music descriptors included in-the-box and signal processing algorithms, is easily expandable and allows for both research experiments and development of large-scale industrial applications.


international acm sigir conference on research and development in information retrieval | 2005

An industrial-strength content-based music recommendation system

Pedro Cano; Markus Koppenberger; Nicolas Wack

We present a metadata free system for the interaction with massive collections of music, the MusicSurfer. MusicSurfer automatically extracts descriptions related to instrumentation, rhythm and harmony from music audio signals. Together with efficient similarity metrics, the descriptions allow navigation of multimillion track music collections in a flexible and efficient way without the need of metadata or human ratings.


international symposium on multimedia | 2009

From Low-Level to High-Level: Comparative Study of Music Similarity Measures

Dmitry Bogdanov; Joan Serrà; Nicolas Wack; Perfecto Herrera

Studying the ways to recommend music to a user is a central task within the music information research community. From a content-based point of view, this task can be regarded as obtaining a suitable distance measurement between songs defined on a certain feature space. We propose two such distance measures. First, a low-level measure based on tempo-related aspects, and second, a high-level semantic measure based on regression by support vector machines of different groups of musical dimensions such as genre and culture, moods and instruments, or rhythm and tempo. We evaluate these distance measures against a number of state-of-the-art measures objectively, based on 17 ground truth musical collections, and subjectively, based on 12 listeners’ ratings. Results show that, in spite of being conceptually different, the proposed methods achieve comparable or even higher performance than the considered baseline approaches. Furthermore, they open up the possibility to explore distance metrics that are based on truly semantic notions.


Proceedings of the Fourth International Conference onWeb Delivering of Music, 2004. EDELMUSIC 2004. | 2004

MTG-DB: a repository for music audio processing

Pedro Cano; Markus Koppenberger; Sira Ferradans; Álvaro MartÍnez; Fabien Gouyon; Vegard Sandvold; Vadim Tarasov; Nicolas Wack

Content-based audio processing researchers need audio and its related metadata to develop and test algorithms. We present a common repository of audio, metadata, ontologies and algorithms. We detail the hardware implementation, in the form of massive storage and computation cluster, the software and databases design and the ontology management of the current system. The repository, as far as copyright licenses allow, is open to researchers outside the music technology group to test and evaluate their algorithms.


intelligent information systems | 2005

Nearest-neighbor automatic sound annotation with a WordNet taxonomy

Pedro Cano; Markus Koppenberger; Sylvain Le Groux; Julien Ricard; Nicolas Wack; Perfecto Herrera

Sound engineers need to access vast collections of sound effects for their film and video productions. Sound effects providers rely on text-retrieval techniques to give access to their collections. Currently, audio content is annotated manually, which is an arduous task. Automatic annotation methods, normally fine-tuned to reduced domains such as musical instruments or limited sound effects taxonomies, are not mature enough for labeling with great detail any possible sound. A general sound recognition tool would require first, a taxonomy that represents the world and, second, thousands of classifiers, each specialized in distinguishing little details. We report experimental results on a general sound annotator. To tackle the taxonomy definition problem we use WordNet, a semantic network that organizes real world knowledge. In order to overcome the need of a huge number of classifiers to distinguish many different sound classes, we use a nearest-neighbor classifier with a database of isolated sounds unambiguously linked to WordNet concepts. A 30% concept prediction is achieved on a database of over 50,000 sounds and over 1600 concepts.


international symposium/conference on music information retrieval | 2013

Essentia: an audio analysis library for music information retrieval

Dmitry Bogdanov; Nicolas Wack; Emilia Gómez; Sankalp Gulati; Perfecto Herrera; Oscar Mayor; Gerard Roma; Justin Salamon; José R. Zapata; Xavier Serra


IEEE Transactions on Multimedia | 2011

Unifying Low-Level and High-Level Music Similarity Measures

Dmitry Bogdanov; Joan Serrà; Nicolas Wack; Perfecto Herrera; Xavier Serra


Archive | 2006

ISMIR 2004 Audio Description Contest

Pedro Cano; Emilia Gómez; Fabien Gouyon; Perfecto Herrera; Markus Koppenberger; Beesuan Ong; Xavier Serra; Sebastian Streich; Nicolas Wack


Journal of The Audio Engineering Society | 2004

Nearest-neighbor Generic Sound Classification with a WordNet-based Taxonomy

Pedro Cano; Markus Koppenberger; Perfecto Herrera; Sylvain Le Groux; Julien Ricard; Nicolas Wack

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Pedro Cano

Pompeu Fabra University

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Xavier Serra

Pompeu Fabra University

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