Search Results - "Benetos, Emmanouil"

Detection and Classification of Acoustic Scenes and Events by Stowell, Dan, Giannoulis, Dimitrios, Benetos, Emmanouil, Lagrange, Mathieu, Plumbley, Mark D.

“…For intelligent systems to make best use of the audio modality, it is important that they can recognize not just speech and music, which have been researched…”
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An End-to-End Neural Network for Polyphonic Piano Music Transcription by Sigtia, Siddharth, Benetos, Emmanouil, Dixon, Simon

“…We present a supervised neural network model for polyphonic piano music transcription. The architecture of the proposed model is analogous to speech…”
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Automatic music transcription: challenges and future directions by Benetos, Emmanouil, Dixon, Simon, Giannoulis, Dimitrios, Kirchhoff, Holger, Klapuri, Anssi

“…Automatic music transcription is considered by many to be a key enabling technology in music signal processing. However, the performance of transcription…”
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Detection and Classification of Acoustic Scenes and Events: Outcome of the DCASE 2016 Challenge by Mesaros, Annamaria, Heittola, Toni, Benetos, Emmanouil, Foster, Peter, Lagrange, Mathieu, Virtanen, Tuomas, Plumbley, Mark D.

“…Public evaluation campaigns and datasets promote active development in target research areas, allowing direct comparison of algorithms. The second edition of…”
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Measuring national mood with music: using machine learning to construct a measure of national valence from audio data by Benetos, Emmanouil, Ragano, Alessandro, Sgroi, Daniel, Tuckwell, Anthony

“…We propose a new measure of national valence based on the emotional content of a country’s most popular songs. We first trained a machine learning model using…”
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Adaptive Noise Reduction for Sound Event Detection Using Subband-Weighted NMF by Zhou, Qing, Feng, Zuren, Benetos, Emmanouil

“…Sound event detection in real-world environments suffers from the interference of non-stationary and time-varying noise. This paper presents an adaptive noise…”
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SubSpectralNet - Using Sub-spectrogram Based Convolutional Neural Networks for Acoustic Scene Classification by Phaye, Sai Samarth R, Benetos, Emmanouil, Wang, Ye

“…Acoustic Scene Classification (ASC) is one of the core research problems in the field of Computational Sound Scene Analysis. In this work, we present…”
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A computational study on outliers in world music by Panteli, Maria, Benetos, Emmanouil, Dixon, Simon

“…The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music…”
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On-Bird Sound Recordings: Automatic Acoustic Recognition of Activities and Contexts by Stowell, Dan, Benetos, Emmanouil, Gill, Lisa F.

“…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…”
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Towards Complete Polyphonic Music Transcription: Integrating Multi-Pitch Detection and Rhythm Quantization by Nakamura, Eita, Benetos, Emmanouil, Yoshii, Kazuyoshi, Dixon, Simon

“…Most work on automatic transcription produces "piano roll" data with no musical interpretation of the rhythm or pitches. We present a polyphonic transcription…”
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PiJAMA: Piano Jazz with Automatic MIDI Annotations by Edwards, Drew, Dixon, Simon, Benetos, Emmanouil

“…Recent advances in automatic piano transcription have enabled large scale analysis of piano music in the symbolic domain. However, the research has largely…”
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Comparison of Feature Extraction Methods for Sound-Based Classification of Honey Bee Activity by Terenzi, Alessandro, Ortolani, Nicola, Nolasco, Ines, Benetos, Emmanouil, Cecchi, Stefania

“…Honey bees are one of the most important insects on the planet since they play a key role in the pollination services of both cultivated and spontaneous flora…”
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Detection and classification of acoustic scenes and events: An IEEE AASP challenge by Giannoulis, Dimitrios, Benetos, Emmanouil, Stowell, Dan, Rossignol, Mathias, Lagrange, Mathieu, Plumbley, Mark D.

“…This paper describes a newly-launched public evaluation challenge on acoustic scene classification and detection of sound events within a scene. Systems…”
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Deep Learning for Black-Box Modeling of Audio Effects by Martínez Ramírez, Marco A., Benetos, Emmanouil, Reiss, Joshua D.

“…Virtual analog modeling of audio effects consists of emulating the sound of an audio processor reference device. This digital simulation is normally done by…”
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Automatic Transcription of Polyphonic Vocal Music by McLeod, Andrew, Schramm, Rodrigo, Steedman, Mark, Benetos, Emmanouil

“…This paper presents a method for automatic music transcription applied to audio recordings of a cappella performances with multiple singers. We propose a…”
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A review of manual and computational approaches for the study of world music corpora by Panteli, Maria, Benetos, Emmanouil, Dixon, Simon

“…The comparison of world music cultures has been a recurring topic in the field of musicology since the end of the nineteenth century. Recent advances in…”
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Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription by Ycart, Adrien, Liu, Lele, Benetos, Emmanouil, Pearce, Marcus T.

“…Automatic Music Transcription (AMT) is usually evaluated using low-level criteria, typically by counting the number of errors, with equal weighting. Yet, some…”
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Polyphonic Sound Event and Sound Activity Detection: A Multi-Task Approach by Pankajakshan, Arjun, Bear, Helen L., Benetos, Emmanouil

“…Polyphonic Sound Event Detection (SED) in real-world recordings is a challenging task because of the dynamic polyphony level, intensity, and duration of sound…”
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Computationally Efficient and Robust BIC-Based Speaker Segmentation by Kotti, M., Benetos, E., Kotropoulos, C.

“…An algorithm for automatic speaker segmentation based on the Bayesian information criterion (BIC) is presented. BIC tests are not performed for every window…”
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Multiple-instrument polyphonic music transcription using a temporally constrained shift-invariant model by Benetos, Emmanouil, Dixon, Simon

“…A method for automatic transcription of polyphonic music is proposed in this work that models the temporal evolution of musical tones. The model extends the…”
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