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 E. Benetos

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Average citations per article3.38
Citation Count54
Publication count16
Publication years2007-2017
Available for download7
Average downloads per article82.86
Downloads (cumulative)580
Downloads (12 Months)483
Downloads (6 Weeks)42
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16 results found Export Results: bibtexendnoteacmrefcsv

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1
June 2017 IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP): Volume 25 Issue 6, June 2017
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 3,   Downloads (12 Months): 13,   Downloads (Overall): 13

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We introduce a novel approach to studying animal behavior and the context in which it occurs, through the use of microphone backpacks carried on the backs of individual free-flying birds. These sensors are increasingly used by animal behavior researchers to study individual vocalizations of freely behaving animals, even in the ...

2
June 2017 IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP): Volume 25 Issue 6, June 2017
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 2,   Downloads (12 Months): 8,   Downloads (Overall): 8

Full text available: PDFPDF
In this paper, a system for polyphonic sound event detection and tracking is proposed, based on spectrogram factorization techniques and state space models. The system extends probabilistic latent component analysis PLCA and is modeled around a four-dimensional spectral template dictionary of frequency, sound event class, exemplar index, and sound state. ...

3 published by ACM
January 2017 Journal on Computing and Cultural Heritage (JOCCH) - Special Issue on Digital Infrastructure for Cultural Heritage, Part 1: Volume 10 Issue 1, April 2017
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 18,   Downloads (12 Months): 307,   Downloads (Overall): 307

Full text available: PDFPDF
In musicology and music research generally, the increasing availability of digital music, storage capacities, and computing power enable and require new and intelligent systems. In the transition from traditional to digital musicology, many techniques and tools have been developed for the analysis of individual pieces of music, but large-scale music ...
Keywords: Digital musicology, music information retrieval, big data, semantic web

4
October 2016 IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP): Volume 24 Issue 10, October 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 1,   Downloads (12 Months): 12,   Downloads (Overall): 12

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This paper introduces a model for simulating environmental acoustic scenes that abstracts temporal structures from audio recordings. This model allows us to explicitly control key morphological aspects of the acoustic scene and to isolate their impact on the performance of the system under evaluation. Thus, more information can be gained ...

5
May 2016 IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP): Volume 24 Issue 5, May 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 15,   Downloads (12 Months): 113,   Downloads (Overall): 130

Full text available: PDFPDF
We present a supervised neural network model for polyphonic piano music transcription. The architecture of the proposed model is analogous to speech recognition systems and comprises an acoustic model and a music language model . The acoustic model is a neural network used for estimating the probabilities of pitches in ...
Keywords: deep learning, automatic music transcription, music language models, recurrent neural networks

6 published by ACM
September 2014 DLfM '14: Proceedings of the 1st International Workshop on Digital Libraries for Musicology
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 1,   Downloads (12 Months): 7,   Downloads (Overall): 26

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Conducting experiments on large scale musical datasets often requires the definition of a dataset as a first step in the analysis process. This is a classification task, but metadata providing the relevant information is not always available or reliable and manual annotation can be prohibitively expensive. In this study we ...

7 published by ACM
September 2014 DLfM '14: Proceedings of the 1st International Workshop on Digital Libraries for Musicology
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 2,   Downloads (12 Months): 23,   Downloads (Overall): 84

Full text available: PDFPDF
Digital music libraries and collections are growing quickly and are increasingly made available for research. We argue that the use of large data collections will enable a better understanding of music performance and music in general, which will benefit areas such as music search and recommendation, music archiving and indexing, ...

8
December 2013 Journal of Intelligent Information Systems: Volume 41 Issue 3, December 2013
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 20

Automatic music transcription is considered by many to be a key enabling technology in music signal processing. However, the performance of transcription systems is still significantly below that of a human expert, and accuracies reported in recent years seem to have reached a limit, although the field is still very ...
Keywords: Automatic music transcription, Music information retrieval, Music signal analysis

9
December 2012 Computer Music Journal: Volume 36 Issue 4, Winter 2012
Publisher: MIT Press
Bibliometrics:
Citation Count: 8

In this work, a probabilistic model for multiple-instrument automatic music transcription is proposed. The model extends the shift-invariant probabilistic latent component analysis method, which is used for spectrogram factorization. Proposed extensions support the use of multiple spectral templates per pitch and per instrument source, as well as a time-varying pitch ...

10
March 2012 LVA/ICA'12: Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

In this paper, a method for multi-pitch detection which exploits the temporal evolution of musical sounds is presented. The proposed method extends the shift-invariant probabilistic latent component analysis algorithm by introducing temporal constraints using multiple Hidden Markov Models, while supporting multiple-instrument spectral templates. Thus, this model can support the representation ...
Keywords: probabilistic latent component analysis, hidden Markov models, music signal analysis

11
November 2010 IEEE Transactions on Audio, Speech, and Language Processing: Volume 18 Issue 8, November 2010
Publisher: IEEE Press
Bibliometrics:
Citation Count: 5

Music genre classification techniques are typically applied to the data matrix whose columns are the feature vectors extracted from music recordings. In this paper, a feature vector is extracted using a texture window of one sec, which enables the representation of any 30 sec long music recording as a time ...
Keywords: non-negative tensor factorization, Bregman divergences, music genre classification

12
November 2010 IEEE Transactions on Audio, Speech, and Language Processing: Volume 18 Issue 8, November 2010
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well ...
Keywords: onset detection, Auditory spectrum, group delay function

13
November 2010 IEEE Transactions on Audio, Speech, and Language Processing: Volume 18 Issue 8, November 2010
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

Music genre classification techniques are typically applied to the data matrix whose columns are the feature vectors extracted from music recordings. In this paper, a feature vector is extracted using a texture window of one sec, which enables the representation of any 30 sec long music recording as a time ...
Keywords: Bregman divergences, music genre classification, non-negative tensor factorization

14
November 2010 IEEE Transactions on Audio, Speech, and Language Processing: Volume 18 Issue 8, November 2010
Publisher: IEEE Press
Bibliometrics:
Citation Count: 2

In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well ...
Keywords: auditory spectrum, onset detection, group delay function

15
July 2008 IEEE Transactions on Audio, Speech, and Language Processing: Volume 16 Issue 5, July 2008
Publisher: IEEE Press
Bibliometrics:
Citation Count: 8

An algorithm for automatic speaker segmentation based on the Bayesian information criterion (BIC) is presented. BIC tests are not performed for every window shift, as previously, but when a speaker change is most probable to occur. This is done by estimating the next probable change point thanks to a model ...
Keywords: Automatic speaker segmentation, inverse Gaussian distribution, simultaneous diagonalization, speaker utterance duration distribution, Bayesian information criterion (BIC), speech analysis

16
December 2007 Neurocomputing: Volume 71 Issue 1-3, December, 2007
Publisher: Elsevier Science Publishers B. V.
Bibliometrics:
Citation Count: 1

A novel framework for audio-assisted dialogue detection based on indicator functions and neural networks is investigated. An indicator function defines that an actor is present at a particular time instant. The cross-correlation function of a pair of indicator functions and the magnitude of the corresponding cross-power spectral density are fed ...
Keywords: Cross-power spectral density, Dialogue detection, Cross-correlation, Indicator functions



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