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Titlebook: Deep Learning Approaches for Spoken and Natural Language Processing; Virender Kadyan,Amitoj Singh,Laith Abualigah Book 2021 The Editor(s)

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發(fā)表于 2025-3-21 19:55:23 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Deep Learning Approaches for Spoken and Natural Language Processing
編輯Virender Kadyan,Amitoj Singh,Laith Abualigah
視頻videohttp://file.papertrans.cn/265/264570/264570.mp4
概述Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications.Presents and escalates the research tre
叢書(shū)名稱Signals and Communication Technology
圖書(shū)封面Titlebook: Deep Learning Approaches for Spoken and Natural Language Processing;  Virender Kadyan,Amitoj Singh,Laith Abualigah Book 2021 The Editor(s)
描述This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work..Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications;.Presents and escalates the research trends and future direction of language and speech processing;.Includes theoretical research, experimental results, and applications of deep learning..
出版日期Book 2021
關(guān)鍵詞Handwriting Recognition; Pattern Recognition; Speech Recognition; Spoken Language Processing; Writer Ide
版次1
doihttps://doi.org/10.1007/978-3-030-79778-2
isbn_softcover978-3-030-79780-5
isbn_ebook978-3-030-79778-2Series ISSN 1860-4862 Series E-ISSN 1860-4870
issn_series 1860-4862
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 20:30:29 | 只看該作者
Signals and Communication Technologyhttp://image.papertrans.cn/d/image/264570.jpg
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發(fā)表于 2025-3-22 01:45:02 | 只看該作者
Deep Learning Approaches for Spoken and Natural Language Processing978-3-030-79778-2Series ISSN 1860-4862 Series E-ISSN 1860-4870
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發(fā)表于 2025-3-22 04:49:07 | 只看該作者
https://doi.org/10.1007/978-3-030-79778-2Handwriting Recognition; Pattern Recognition; Speech Recognition; Spoken Language Processing; Writer Ide
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Xiao Guo,Zhenjiang Shen,Xiao Teng,Yong Linmultiple choice and true/false questions because the answers are specific compared with essay question answers. Automatic grading system (AGS) was developed to evaluate essay answers using a computer program that solves manual grading process problems like high cost, time-consuming task, increasing
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Junjie Li,Shuo Tian,Yuanhui Liu corresponding to every vowel for the improved efficiency of Automatic Speech Recognition (ASR) system. In this research, the linguistic study of native speakers and their auditory inconsistency was pursued using the extraction of efficient front-end speech vectors utilizing three varying fractal di
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