Introduction to Japanese Natural Language Processing

Web Name: Introduction to Japanese Natural Language Processing






Introduction to Japanese Natural Language Processing

Masato Hagiwara and Paul O'Leary McCann Completion: Winter 2021 (expected). Available in both English and Japanese Buy on Leanpub Learn More

About This Book

A thorough guide for programmers working with Japanese text, covering fundamental issues like tokenization and recent research topics like generating natural language texts.Working examples are accompanied by extensive reference to allow problem solving even without a background in Japanese or Machine Learning.

Basics of Japanese Linguistics

All the background knowledge required for processing Japanese language texts on computers — characters, words, grammar, as well as encodings and emoji.

Open-source Tools

Use open-source tools to analyze Japanese texts, including: word tokenization with MeCab, PoS tagging and parsing with spaCy.

Dictionaries & Datasets

A thorough overview of dictionaries, corpora, and other datasets commonly used for Japanese language processing.

Word Embeddings

Use word and sentence embeddings to represent, visualize, and retrieve Japanese texts.

Language Generation and Conversion

Use neural networks to generate Japanese texts and and convert between Kana and Kanji.

Natural Language Understanding

Use transfer learning to understand Japanese texts through sentiment analysis and named entity recognition.

Who This Book Is For

This book is written for anyone who's interested in dealing with Japanese texts, including software developers, AI researchers and engineers, and language experts.

No Math Required

You don't need to know math to understand the book. We focus on how to use tools to get things done, rather than explaining the theory behind their implementation.

No Japanese Required

While highly desirable, you don't need to understand Japanese to read the book, and example texts will be thoroughly annotated.

Basic Python

The only prerequiste for this book is basic Python skills. Extensive code examples are used to show how to approach and solve problems.

Table of Contents

Chapter 1: Basics of Japanese linguistics1.1 Japanese language overview1.2 Orthography: What kinds of letters are there?1.3 Morphology: What kinds of words are there?1.4 Syntax: How are sentences structured?1.5 Technical Notes: How are texts represented? Chapter 2: Morphological analysis and open-source tools2.1 Tokenizers and morphological analyzers: overview and basic use2.2 Advanced tokenization2.3 Dependency parsers Chapter 3: Datasets3.1 Overview3.2 Dictionaries3.3 General Corpora3.4 Specialized Corpora Chapter 4: Word and sentence embeddings4.1 Word embeddings4.2 Sentence embeddings4.3 Multilingual embeddings Chapter 5: Natural language generation and conversion with Transformer5.1 Introduction to Transformer5.2 Text generation5.3 Kana-Kanji conversion / transliteration Chapter 6: Natural language understanding via transfer learning6.1 Introduction to transfer learning6.2 Sentiment / document classification6.3 Named entity recognition

About The Authors

Masato Hagiwara is an independent NLP/ML researcher and engineer at Octanove Labs.He works on educational and Asian language processing projects with world class startups and research institutes. He received his Ph.D. degree in Information Science from Nagoya University in 2009, and worked at companies including Google, Microsoft Research, Baidu, and Duolingo.An author of several best-selling NLP books.

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Paul O'Leary McCann is a consultant and member of the spaCy development team. Basedin Tokyo since 2011, he maintains the most popular Japanese tokenizer inPython. Outside of his work on NLP he helps out with Tokyo Indies, a monthlygame developer meetup.

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