End-to-End Acoustic Modeling Using Convolutional Neural Networks
Vishal Passricha; Rajesh Kumar Aggarwal National Institute of Technology Kurukshetra, Kurukshetra, India
Abstract
State-of-the-art automatic speech recognition (ASR) systems map speech into its corresponding text. Conventional ASR systems model the speech signal into phones in two steps; feature extraction and classifier training. Traditional ASR systems have been replaced by deep neural network (DNN)-based systems. Today, end-to-end ASRs are gaining in popularity due to simplified model-building processes and the ability to directly map speech into text without predefined alignments. These models are based on data-driven learning methods and competition with complicated ...
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