Topic
Language technology
About: Language technology is a research topic. Over the lifetime, 4948 publications have been published within this topic receiving 164173 citations. The topic is also known as: human language technology.
Papers published on a yearly basis
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Papers
TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
Abstract: In this article we discuss our experience designing and implementing a statistical computing language. In developing this new language, we sought to combine what we felt were useful features from two existing computer languages. We feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scoping.
10,904 citations
Book•
1 Jan 1982
TL;DR: It is concluded that language acquisition occurs best when language is used for the purpose for which it was designed: communication.
Abstract: This text explores the relationship between second language teaching practice and what is known about the process of second language acquisition and summarizes the current state of second language acquisition theory.-- Draws general conclusions about the application of theory to methods and materials and describes the characteristics that effective materials should include.-- Concludes that language acquisition occurs best when language is used for the purpose for which it was designed: communication.
7,553 citations
Book•
1 Jan 2000
TL;DR: This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora, to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation.
Abstract: From the Publisher:
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
4,732 citations
Book•
12 Jun 2009TL;DR: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.
Abstract: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
4,331 citations
Book•
1 Dec 1999
TL;DR: It is now clear that HAL's creator, Arthur C. Clarke, was a little optimistic in predicting when an artificial agent such as HAL would be avail-able as discussed by the authors.
Abstract: is one of the most recognizablecharacters in 20th century cinema. HAL is an artificial agent capable of such advancedlanguage behavior as speaking and understanding English, and at a crucial moment inthe plot, even reading lips. It is now clear that HAL’s creator, Arthur C. Clarke, wasa little optimistic in predicting when an artificial agent such as HAL would be avail-able. But just how far off was he? What would it take to create at least the language-relatedpartsofHAL?WecallprogramslikeHALthatconversewithhumansinnatural
4,289 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 9 |
| 2024 | 9 |
| 2023 | 13 |
| 2022 | 21 |
| 2021 | 49 |
| 2020 | 75 |