Neural Machine Translation
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Neural Machine Translation
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Author : Philipp Koehn
language : en
Publisher: Cambridge University Press
Release Date : 2020-06-18
Neural Machine Translation written by Philipp Koehn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-18 with Computers categories.
Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.
Joint Training For Neural Machine Translation
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Author : Yong Cheng
language : en
Publisher:
Release Date : 2019
Joint Training For Neural Machine Translation written by Yong Cheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Machine translating categories.
This book presents four approaches to jointly training bidirectional neural machine translation (NMT) models. First, in order to improve the accuracy of the attention mechanism, it proposes an agreement-based joint training approach to help the two complementary models agree on word alignment matrices for the same training data. Second, it presents a semi-supervised approach that uses an autoencoder to reconstruct monolingual corpora, so as to incorporate these corpora into neural machine translation. It then introduces a joint training algorithm for pivot-based neural machine translation, which can be used to mitigate the data scarcity problem. Lastly it describes an end-to-end bidirectional NMT model to connect the source-to-target and target-to-source translation models, allowing the interaction of parameters between these two directional models.
Neural Machine Translation For Multimodal Interaction
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Author : Koel Dutta Chowdhury
language : en
Publisher:
Release Date : 2019
Neural Machine Translation For Multimodal Interaction written by Koel Dutta Chowdhury and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Typically it is seen that multimodal neural machine translation (MNMT) systems trained on a combination of visual and textual inputs produce better translations than systems trained using only textual inputs. The task of such systems can be decomposed into two sub-tasks: learning visually grounded representations from images and translation of the textual counterparts using those representations. In a multi-task learning framework, translations are generated from an attention-based encoder-decoder framework and grounded representations that are learned from pretrained convolutional neural networks (CNNs) for classifying images. In this thesis, I study different computational techniques to translate the meaning of sentences from one language into another considering the visual modality as a naturally occurring meaning representation bridging between languages. We examine the behaviour of state-of-the-art MNMT systems from the data perspective in order to understand the role of the both textual and visual inputs in such systems. We evaluate our models on the Multi30k, a large-scale multilingual multimodal dataset publicly available for machine learning research. Our results in the optimal and sparse data settings show that the differences in translation system performance are proportional to the amount of both visual and linguistic information whereas, in the adversarial condition the effect of the visual modality is rather small or negligible. The chapters of the thesis follow a progression starting with using different state-of-the-art MMT models for incorporating images in optimal data settings to creating synthetic image data under the low-resource scenario and extending to addition of adversarial perturbations to the textual input for evaluating the real contribution of images.
Efficient Neural Machine Translation
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Author : 顾佳涛
language : en
Publisher:
Release Date : 2018
Efficient Neural Machine Translation written by 顾佳涛 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Machine translating categories.
Hands On Natural Language Processing With Python
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Author : Rajesh Arumugam
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-18
Hands On Natural Language Processing With Python written by Rajesh Arumugam and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Computers categories.
Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book.
Machine Translation
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Author : Jiajun Chen
language : en
Publisher: Springer
Release Date : 2019-01-08
Machine Translation written by Jiajun Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-08 with Computers categories.
This book constitutes the refereed proceedings of the 14th China Workshop on Machine Translation, CWMT 2018, held in Wuyishan, China, in October 2018. The 9 papers presented in this volume were carefully reviewed and selected from 17 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Enhanced Neural Machine Translation With External Resources
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Author : 陳冠華
language : en
Publisher:
Release Date : 2022
Enhanced Neural Machine Translation With External Resources written by 陳冠華 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Machine translating categories.
Machine Translation
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Author : Derek F. Wong
language : en
Publisher: Springer
Release Date : 2017-11-13
Machine Translation written by Derek F. Wong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-13 with Computers categories.
This book constitutes the refereed proceedings of the 13th China Workshop on Machine Translation, CWMT 2017, held in Dalian, China, in September 2017. The 10 papers presented in this volume were carefully reviewed and selected from 26 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Learning Machine Translation
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Author : Cyril Goutte
language : en
Publisher: MIT Press
Release Date : 2009
Learning Machine Translation written by Cyril Goutte and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.
Neural Machine Translation With A Unified Framework Of Transferable Models
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Author : 王永
language : en
Publisher:
Release Date : 2020
Neural Machine Translation With A Unified Framework Of Transferable Models written by 王永 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Neural networks (Computer science) categories.