Speech recognition, Artificial intelligence, Mel-frequency cepstrum, Cognitive load and Pattern recognition are his primary areas of study. Julien Epps studies Voice activity detection, a branch of Speech recognition. Bag-of-words model is closely connected to Machine learning in his research, which is encompassed under the umbrella topic of Artificial intelligence.
His Mel-frequency cepstrum study which covers Feature that intersects with Set, Voice analysis, Relation and Contrast. The concepts of his Pattern recognition study are interwoven with issues in Consensus clustering and Data mining. His research integrates issues of Adjusted mutual information and Cluster analysis in his study of Normalization.
Julien Epps mostly deals with Speech recognition, Artificial intelligence, Pattern recognition, Feature extraction and Speaker recognition. His Speech recognition study combines topics from a wide range of disciplines, such as Mixture model, Feature, Emotion classification and Mel-frequency cepstrum. His research in Feature intersects with topics in Depression and Set.
His Artificial intelligence research includes themes of Cognitive load, Machine learning, Computer vision and Natural language processing. His Cognitive load research focuses on subjects like Formant, which are linked to Vocal tract. His studies deal with areas such as Word error rate, Electroencephalography and Signal processing as well as Pattern recognition.
His primary areas of study are Speech recognition, Artificial intelligence, Feature extraction, Depression and Feature. His Manner of articulation study, which is part of a larger body of work in Speech recognition, is frequently linked to Spoofing attack, bridging the gap between disciplines. His Manner of articulation research is multidisciplinary, incorporating elements of Bigram, Normalization, Duration and Vocal tract.
His Artificial intelligence research integrates issues from Machine learning, Categorical variable, Computer vision and Pattern recognition. His research investigates the link between Pattern recognition and topics such as Flexibility that cross with problems in Ranking. His Feature research includes elements of Valence and Set.
His primary areas of investigation include Speech recognition, Artificial intelligence, Feature extraction, Feature and Depression. His work is dedicated to discovering how Speech recognition, Convolutional neural network are connected with Vocal tract and other disciplines. Julien Epps has researched Artificial intelligence in several fields, including Depression score, Machine learning and Task analysis.
His studies in Machine learning integrate themes in fields like Multi-task learning and Speaker recognition. The various areas that he examines in his Feature extraction study include Artificial neural network, Deep learning, Emotion classification and Filter bank. His study focuses on the intersection of Depression and fields such as Stress with connections in the field of Set.
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Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
Nguyen Xuan Vinh;Julien Epps;James Bailey.
Journal of Machine Learning Research (2010)
Information theoretic measures for clusterings comparison: is a correction for chance necessary?
Nguyen Xuan Vinh;Julien Epps;James Bailey.
international conference on machine learning (2009)
The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
Florian Eyben;Klaus R. Scherer;Bjorn W. Schuller;Johan Sundberg.
IEEE Transactions on Affective Computing (2016)
A review of depression and suicide risk assessment using speech analysis
Nicholas Cummins;Stefan Scherer;Jarek Krajewski;Sebastian Schnieder.
Speech Communication (2015)
Signal Processing in Sequence Analysis: Advances in Eukaryotic Gene Prediction
M. Akhtar;J. Epps;E. Ambikairajah.
IEEE Journal of Selected Topics in Signal Processing (2008)
A study of hand shape use in tabletop gesture interaction
Julien Epps;Serge Lichman;Mike Wu.
human factors in computing systems (2006)
The INTERSPEECH 2014 Computational Paralinguistics Challenge: Cognitive & Physical Load
Björn W. Schuller;Stefan Steidl;Anton Batliner;Julien Epps.
conference of the international speech communication association (2014)
An Investigation of Depressed Speech Detection: Features and Normalization.
Nicholas Cummins;Julien Epps;Michael Breakspear;Roland Goecke.
conference of the international speech communication association (2011)
Multimodal assistive technologies for depression diagnosis and monitoring
Jyoti Joshi;Roland Goecke;Roland Goecke;Sharifa Alghowinem;Abhinav Dhall.
Journal on Multimodal User Interfaces (2013)
A new technique for wideband enhancement of coded narrowband speech
J. Epps;W.H. Holmes.
1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351) (1999)
Profile was last updated on December 6th, 2021.
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