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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 ...
A morphological model for simulating acoustic scenes and its application to sound event detection
(IEEE, 2016-07)
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 ...
Automatic transcription and pitch analysis of the British Library World & Traditional Music Collection
(Association Dirac, 2015-06-10)
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 ...
Towards HMM-based glissando detection for recordings of Chinese bamboo flute
(2018-09-23)
Playing techniques such as ornamentations and articulation effects constitute important aspects of music performance. However, their computational analysis is still under-explored due to a lack of data and established ...
Automatic transcription of polyphonic music exploiting temporal evolution
(2012-12-31)
Automatic music transcription is the process of converting an audio recording into a symbolic representation using musical notation. It has numerous applications in music information retrieval, computational musicology, ...
Automatic Transcription of Vocal Quartets
(Centre for Digital Music, Queen Mary University of London, 2016-12-20)
This work presents a probabilistic latent component analysis (PLCA) method applied to automatic music transcription of a cappella performances of vocal quartets. A variable-Q transform (VQT) representation of the audio ...