Filters








6,767 Hits in 7.9 sec

Sequence Representation Of Music Structure Using Higher-Order Similarity Matrix And Maximum-Likelihood Approach

Geoffroy Peeters
2007 Zenodo  
We finally presented a maximum likelihood approach to estimate the structure of the track from the segment detected in the similarity matrix.  ...  We then compare the estimation of the sequences using a 1st order similarity matrix (54.8%) with the estimation using higher-order similarity matrix ("HOS" column).  ... 
doi:10.5281/zenodo.1416748 fatcat:nwpgkxhvsvcqlndo6mwrolwoy4

Hierarchical Sequential Memory For Music: A Cognitive Model

James B. Maxwell, Philippe Pasquier, Arne Eigenfeldt
2009 Zenodo  
The upper-level nodes at L3 and L4 are used to learn high-order musical structure from the motives learned at L2.  ...  "temporal invariance" [5] -i.e., an "S" phrase in SPEAC analysis, and a "head" in the Generative Theory of Tonal Music [9] , both use singular names at higher levels to represent sequences of musical  ... 
doi:10.5281/zenodo.1414849 fatcat:efb6cqkrlbg3neuccy2t47m2fa

Off-line refinement of audio-to-score alignment by observation template adaptation

Cyril Joder, Bjorn Schuller
2013 2013 IEEE International Conference on Acoustics, Speech and Signal Processing  
Experiments run on a large dataset of popular and classical piano music show that such an approach can lead to a significant improvement of the alignment accuracy compared to the use of a single generic  ...  Audio-to-score alignment aims at matching a symbolic representation (the score) to a musical recording.  ...  The observation model used is defined in (2). EM-Based Adaptation The first adaptation strategy aims at estimating the optimal mapping matrix W according to the Maximum Likelihood (ML) criterion.  ... 
doi:10.1109/icassp.2013.6637638 dblp:conf/icassp/JoderS13 fatcat:wqkk7qcm25b2takbeccedzcc64

Music Structure Analysis from Acoustic Signals [chapter]

Roger B. Dannenberg, Masataka Goto
2008 Handbook of Signal Processing in Acoustics  
Repeated phrases and hierarchical structures can be discovered by finding similar sequences of feature vectors within a piece of music.  ...  Structure analysis can be used to construct music summaries and to assist music browsing.  ...  , and correspondence.  ... 
doi:10.1007/978-0-387-30441-0_21 fatcat:phj6h5rnzja5df4vg6nxx2yf7e

Learning Combinations of Multiple Feature Representations for Music Emotion Prediction

Jens Madsen, Bjørn Sand Jensen, Jan Larsen
2015 Proceedings of the 1st International Workshop on Affect & Sentiment in Multimedia  
Music consists of several structures and patterns evolving through time which greatly influences the human decoding of higher-level cognitive aspects of music like the emotions expressed in music.  ...  We show the increased predictive performance using the combination of different features and representations along with the great interpretive prospects of this approach.  ...  However, explaining higher-order cognitive aspects using single features and feature representations is a simplified view of the complex structures found in music.  ... 
doi:10.1145/2813524.2813534 fatcat:xb7koifmgveuvbc5b6pyqdrp5q

Modeling Musical Structure with Artificial Neural Networks [article]

Stefan Lattner
2020 arXiv   pre-print
For learning transformations in sequences, I propose a special predictive training of the GAE, which yields a representation of polyphonic music as a sequence of intervals.  ...  First, using probability estimations of a Restricted Boltzmann Machine (RBM), a probabilistic bottom-up approach to melody segmentation is studied.  ...  This work would not have been possible without the great support of my cosupervisor Maarten Grachten, who has taught me the scientific tools of the trade from the first day of my Ph.D., and since that  ... 
arXiv:2001.01720v1 fatcat:u3sabyxverbgzcm5kh3ek3xcgy

Large-Scale Classification of Structured Objects using a CRF with Deep Class Embedding [article]

Eran Goldman, Jacob Goldberger
2017 arXiv   pre-print
This paper presents a novel deep learning architecture to classify structured objects in datasets with a large number of visually similar categories.  ...  We model sequences of images as linear-chain CRFs, and jointly learn the parameters from both local-visual features and neighboring classes.  ...  even to global maximum likelihood.  ... 
arXiv:1705.07420v2 fatcat:pjcw534dsnbdjmgdrbjoduucsa

Musical expertise is associated with improved neural statistical learning [article]

Jacques Pesnot Lerousseau, Daniele Schon
2020 bioRxiv   pre-print
Overall, our results prove that musical expertise is associated with improved neural SL, and support music-based intervention to fine tune general cognitive abilities.  ...  EEG recordings reveal a neural underpinning of the musicians advantage: the P300 amplitude correlates with the Bayesian model surprise elicited by each item, and so, more strongly for musicians than non-musicians  ...  the maximum of the likelihood is the same as finding the maximum of the log-likelihood.  ... 
doi:10.1101/2020.05.20.106187 fatcat:6bbbchfabvhsffd46vi37wgugq

Comparing Probabilistic Models for Melodic Sequences [chapter]

Athina Spiliopoulou, Amos Storkey
2011 Lecture Notes in Computer Science  
Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of  ...  Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre.  ...  This can result in model samples that have higher interand lower intra-piece similarity than a set of real music sequences.  ... 
doi:10.1007/978-3-642-23808-6_19 fatcat:yumk3virezbgfm3wh6rsq2iwhu

Comparing Probabilistic Models for Melodic Sequences [article]

Athina Spiliopoulou, Amos Storkey
2011 arXiv   pre-print
Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of  ...  Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre.  ...  This can result in model samples that have higher interand lower intra-piece similarity than a set of real music sequences.  ... 
arXiv:1109.6804v1 fatcat:6r3gywwafvc6fkmxdwrahskf6y

Towards Computer-Assisted Flamenco Transcription: An Experimental Comparison of Automatic Transcription Algorithms as Applied to A Cappella Singing

Emilia Gómez, Jordi Bonada
2013 Computer Music Journal  
The proposed approach is evaluated on a music collection of 72 performances, including a variety of singers and recording conditions, and the presence or absence of percussion, background voices, and noise  ...  state the main limitations of our approach and discuss challenges for future studies.  ...  Acknowledgments The authors would like to thank the COFLA team for providing the data set and expertise in flamenco music.  ... 
doi:10.1162/comj_a_00180 fatcat:gjfiq6cvbjg5fdmqi6zjvtpjvm

Sparse representations of polyphonic music

Mark D. Plumbley, Samer A. Abdallah, Thomas Blumensath, Michael E. Davies
2006 Signal Processing  
We consider two approaches for sparse decomposition of polyphonic music: a timedomain approach based on shift-invariant waveforms, and a frequency-domain approach based on phase-invariant power spectra  ...  These results suggest that these two methods would provide a powerful yet complementary approach to automatic music transcription or object-based coding of musical audio.  ...  507142 project SIMAC (Semantic Interaction with Music Audio Contents).  ... 
doi:10.1016/j.sigpro.2005.06.007 fatcat:ggwhbkwe3zhuni2mqmzwo3jdve

Predominant Fundamental Frequency Estimation Vs Singing Voice Separation For The Automatic Transcription Of Accompanied Flamenco Singing

Emilia Gómez, Francisco J. Cañadas-Quesada, Justin Salamon, Jordi Bonada, Pedro Vera-Candeas, Pablo Cabañas Molero
2012 Zenodo  
ACKNOWLEDGEMENTS The authors would like to thank the COFLA 1 team for providing the data set and expert knowledge in flamenco music.  ...  This work has been partially funded by AGAUR (mobility grant), the COFLA project (P09-TIC-4840 Proyecto de Excelencia, Junta de Andalucía) and the Programa de Formación del Profesorado Universitario of  ...  Repeating-structure removal methods [17] use a pattern recognition approach to identify and extract accompaniment segments, without manual labeling, which can be classified as repeating musical structures  ... 
doi:10.5281/zenodo.1416990 fatcat:drdkduhrnvdwjcsvdp6v5qq5xe

On the use of sequential patterns mining as temporal features for music genre classification

Jia-Min Ren, Zhi-Sheng Chen, Jyh-Shing Roger Jang
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
In this paper, we propose the use of a song tokenization method (which transforms the music into a sequence of units) in conjunction with a data mining technique for investigating the long-term structures  ...  Music can be viewed as a sequence of sound events.  ...  The length of the segment becomes an important issue since music is a sequence of con-tinuous and ordered signals.  ... 
doi:10.1109/icassp.2010.5495955 dblp:conf/icassp/RenCJ10 fatcat:zylgiemesjclznatqk4j2uvulm

Unified View of Prediction and Repetition Structure in Audio Signals With Application to Interest Point Detection

Shlomo Dubnov
2008 IEEE Transactions on Audio, Speech, and Language Processing  
We present algorithms for estimation of these measures and create a visualization that displays their temporal structure in musical recordings.  ...  In this paper we present a new method for analysis of musical structure that captures local prediction and global repetition properties of audio signals in one information processing framework.  ...  Moreover, they usually employ synthetic examples of limited musical complexity or naturaleness and rely on musical knowledge in order to correlate musical structure to listener responses.  ... 
doi:10.1109/tasl.2007.912378 fatcat:lgqk4y7xwvgwhlzmlpmj4zh3am
« Previous Showing results 1 — 15 out of 6,767 results