Browsing Centre for Digital Music (C4DM) by Title
Now showing items 72-91 of 210
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An efficient temporally-constrained probabilistic model for multiple-instrument music transcription
(International Society for Music Information Retrieval, 2015-10-26)In this paper, an efficient, general-purpose model for multiple instrument polyphonic music transcription is proposed. The model is based on probabilistic latent component analysis and supports the use of sound state ... -
?` El Caballo Viejo? Latin genre recognition with deep learning and spectral periodicity
(Springer, 2015-06-16)The ``winning'' system in the 2013 MIREX Latin Genre Classification Task was a deep neural network trained with simple features. An explanation for its winning performance has yet to be found. In previous work, we built ... -
?`El Caballo Viejo? Latin Genre Recognition with Deep Learning and Spectral Periodicity
The ``winning'' system in the 2013 MIREX Latin Genre Classification Task was a deep neural network trained with simple features. An explanation for its winning performance has yet to be found. In previous work, we built ... -
An End-to-End Neural Network for Polyphonic Music Transcription
(arxiv, 2015-08)We present a neural network model for polyphonic music transcription. The architecture of the proposed model is analogous to speech recognition systems and comprises an acoustic model and a music language mode}. The acoustic ... -
An End-to-End Neural Network for Polyphonic Piano Music Transcription
(IEEE, 2016-02)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 ... -
Ensemble Models for Spoofing Detection in Automatic Speaker Verification
(International Speech Communication Association (ISCA), 2019-09-15)Detecting spoofing attempts of automatic speaker verification (ASV) systems is challenging, especially when using only one modelling approach. For robustness, we use both deep neural networks and traditional machine learning ... -
An evaluation framework for event detection using a morphological model of acoustic scenes
(arxiv, 2015-01)This paper introduces a model of environmental acoustic scenes which adopts a morphological approach by ab-stracting temporal structures of acoustic scenes. To demonstrate its potential, this model is employed to evaluate ... -
Evolution of Music by Public Choice
(2012-07-24)Music evolves as composers, performers, and consumers favor some musical variants over others. To investigate the role of consumer selection, we constructed a Darwinian music engine consisting of a population of short audio ... -
The evolution of popular music: USA 1960-2010.
(2015-05)In modern societies, cultural change seems ceaseless. The flux of fashion is especially obvious for popular music. While much has been written about the origin and evolution of pop, most claims about its history are anecdotal ... -
Explaining Predictions of Machine Listening Systems
(Centre for Digital Music, Queen Mary University of London, 2016-12-20)We adapt local, interpretable and model-agnostic explanations [1] for use with a machine listening system, and demonstrate it for singing voice detection. Such explanations provide ways to understand the behaviour of machine ... -
An extensible cluster-graph taxonomy for open set sound scene analysis
(2018-11-19)We present a new extensible and divisible taxonomy for open set sound scene analysis. This new model allows complex scene analysis with tangible descriptors and perception labels. Its novel structure is a cluster graph ... -
FEATUR.UX: An approach to leveraging multitrack information for artistic music visualization
FEATUR.UX (Feature - ous) is an audio visualisation tool, currently in the process of development, which proposes to introduce a new approach to sound visualisation using pre-mixed, independent multitracks and audio feature ...