Paper Title

Survey on Deep Neural Networks in Speech using Natural Language Processing

Authors

Suvarna D. Pingle

Keywords

speech processing, computational intelligence, deep learning, computer vision, natural language processing, hardware constraints, embedded systems, convolutional neural networks, deep auto-encoders, recurrent neural networks.

Abstract

This overview presents a survey of cutting edge profound neural system designs, calculations, and frameworks in vision and discourse applications. Late advances in profound fake neural system calculations and structures have prodded quick development and improvement of insightful vision and discourse frameworks. With accessibility of tremendous measures of sensor information and distributed computing for preparing and preparing of profound neural systems, and with expanded advancement in portable and installed innovation, the cutting edge smart frameworks are ready to upset individual and business registering. This study starts by giving foundation and development of probably the best profound learning models for astute vision and discourse frameworks to date. A diagram of huge scope mechanical innovative work endeavors is given to underscore future patterns and prospects of canny vision and discourse frameworks. Powerful and productive clever frameworks request low-idleness and high loyalty in asset obliged equipment stages, for example, cell phones, robots, and autos. Hence, this study likewise gives a synopsis of key difficulties and late accomplishments in running profound neural systems on equipment limited stages, for example inside restricted memory, battery life, and handling capacities. At long last, developing utilizations of vision and discourse across orders, for example, full of feeling figuring, smart transportation, and accuracy medication are examined. As far as anyone is concerned, this paper gives one of the most extensive reviews on the most recent advancements in shrewd vision and discourse applications from the viewpoints of both programming and equipment frameworks. Huge numbers of these rising innovations utilizing profound neural systems show gigantic guarantee to change innovative work for future vision and discourse frameworks.

How To Cite

"Survey on Deep Neural Networks in Speech using Natural Language Processing", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 9, page no.70 - 77, September-2020, Available :https://ijsdr.org/papers/IJSDR2009013.pdf

Issue

Volume 5 Issue 9, September-2020

Pages : 70 - 77

Other Publication Details

Paper Reg. ID: IJSDR_192426

Published Paper Id: IJSDR2009013

Downloads: 000347199

Research Area: Engineering

Country: -, -, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR2009013

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2009013

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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