Simon Dixon mainly focuses on Speech recognition, Artificial intelligence, Algorithm, Music information retrieval and Rhythm. Simon Dixon has researched Speech recognition in several fields, including Chord, Transcription, Musical, MIDI and Beat. Artificial intelligence connects with themes related to Pattern recognition in his study.
His work in the fields of Algorithm, such as Source separation, overlaps with other areas such as Frame. The Music information retrieval study combines topics in areas such as Multimedia, Transcription, Pop music automation, Data science and Audio signal. His Rhythm study integrates concerns from other disciplines, such as Timbre, World Wide Web, Audio analyzer and Metaphor.
His primary areas of investigation include Speech recognition, Artificial intelligence, Pattern recognition, Musical and Music information retrieval. His research in Speech recognition intersects with topics in Transcription, Beat, Rhythm and Piano. Simon Dixon has included themes like Time signature and Beat detection in his Beat study.
His work carried out in the field of Artificial intelligence brings together such families of science as Chord, Machine learning and Natural language processing. His work in Pattern recognition covers topics such as Source separation which are related to areas like Adversarial system and Artificial neural network. His Music information retrieval research is multidisciplinary, incorporating elements of Multimedia and Data science.
Simon Dixon spends much of his time researching Artificial intelligence, Pattern recognition, Speech recognition, Source separation and Singing. His Artificial intelligence research is multidisciplinary, relying on both Context and Machine learning. His Context research incorporates themes from Music information retrieval and Identification.
His study on Speech recognition also encompasses disciplines like
Artificial intelligence, Singing, Pattern recognition, Speech recognition and Transcription are his primary areas of study. His research brings together the fields of Machine learning and Artificial intelligence. His Singing research includes elements of Bass, Pitch error, Active listening, Absolute pitch and Pitch variation.
He interconnects Artificial neural network, Deep learning, Automatic learning and Kernel in the investigation of issues within Pattern recognition. His study in Speech recognition is interdisciplinary in nature, drawing from both Inference, Melody, Musical, Task analysis and Human intelligence. His Transcription study incorporates themes from Pronunciation, Language model, Musical notation, Knowledge representation and reasoning and Lyrics.
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Automatic Extraction of Tempo and Beat From Expressive Performances
Journal of New Music Research (2001)
Automatic music transcription: challenges and future directions
Emmanouil Benetos;Simon Dixon;Dimitrios Giannoulis;Holger Kirchhoff.
intelligent information systems (2013)
An experimental comparison of audio tempo induction algorithms
F. Gouyon;A. Klapuri;S. Dixon;M. Alonso.
IEEE Transactions on Audio, Speech, and Language Processing (2006)
An end-to-end neural network for polyphonic piano music transcription
Siddharth Sigtia;Emmanouil Benetos;Simon Dixon.
IEEE Transactions on Audio, Speech, and Language Processing (2016)
PYIN: A fundamental frequency estimator using probabilistic threshold distributions
Matthias Mauch;Simon Dixon.
international conference on acoustics, speech, and signal processing (2014)
Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation
Daniel Stoller;Sebastian Ewert;Simon Dixon.
international symposium/conference on music information retrieval (2018)
A Review of Automatic Rhythm Description Systems
Fabien Gouyon;Simon Dixon.
Computer Music Journal (2005)
APPROXIMATE NOTE TRANSCRIPTION FOR THE IMPROVED IDENTIFICATION OF DIFFICULT CHORDS
Matthias Mauch;Simon Dixon.
international symposium/conference on music information retrieval (2010)
Evaluation of the Audio Beat Tracking System BeatRoot
Journal of New Music Research (2007)
MATCH: A Music Alignment Tool Chest
Simon Dixon;Gerhard Widmer.
international symposium/conference on music information retrieval (2005)
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