A Hybrid Deep Ensemble for Speech Disfluency Classification

In this paper, a novel Hybrid Deep Ensemble (HDE) is proposed for automatic speech disfluency classification on a sparse speech dataset. Categorizations of speech disfluencies for diagnosis of speech disorders have so long relied on sophisticated deep learning models. Such a task can be accomplished...

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Veröffentlicht in:	Circuits, systems, and signal processing systems, and signal processing, 2021-08, Vol.40 (8), p.3968-3995
Hauptverfasser:	Pravin, Sheena Christabel, Palanivelan, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Artificial neural networks Circuits and Systems Classification Deep learning Electrical Engineering Electronics and Microelectronics Engineering Instrumentation Machine learning Model accuracy Signal,Image and Speech Processing Speech
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