Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/730
Title: Semi supervised accent invariant speech recognition
Authors: Venkadeswaran, Aravaida Kumaran
Anand, Saket (Advisor)
Keywords: Automatic Speech Recognition
Semi Supervision
Domain Adaptation
Speech
Ac- cent Invariance
Word embeddings
Unsupervised
Speech2Vec
Raw Speech
Issue Date: 28-Apr-2019
Publisher: IIITD-Delhi
Abstract: Automatic Speech Recognition which is aimed at enabling a more natural form of human-machine interaction has been an area of research for decades now and many breakthroughs have been made in this eld. The performance of many state-of-the-art systems for mainstream languages and accents are extremely good. And there is a need for zero-resource or minimal resource systems as gathering enough data is highly challenging and sometimes near impossible. Through this study, we aim to provide a proof of concept for the idea of using speech embeddings for Automatic Speech Recognition.
URI: http://repository.iiitd.edu.in/xmlui/handle/123456789/730
Appears in Collections:Year-2019

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