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Association for Computing Machinery

Articles Tagged: Natural language processing

Articles & Features

DEPARTMENT: Labz

Building a Pipeline for Real-Time Topical Polling: Grove City College

By Kenneth Browder, Jonathan Allarassem, May 2024

PDF | HTML | In the Digital Library

SECTION: Features

ChatGPT for Next Generation Science Learning

This article pilots ChatGPT in tackling the most challenging part of science learning and found it successful in automation of assessment development, grading, learning guidance, and recommendation of learning materials.

By Xiaoming Zhai, April 2023

PDF | HTML | In the Digital Library

ChatGPT in Education: Partner or Pariah?

ChatGPT has taken the world by storm, with educators reeling from its implication for curricula and assessment. This article examines how ChatGPT resembles earlier technologies and predicts how we can expect it to impact education going forward.

By David A. Joyner, April 2023

PDF | HTML | In the Digital Library

DEPARTMENT: Hello World

The Inexplicable Efficacy of Language Models

By Rachith Aiyappa, Zoher Kachwala, April 2023

PDF | HTML | In the Digital Library

SECTION: Features

How to tame your chatbot

The best way to stop a bad chatbot spreading misinformation may be a good chatbot providing facts. But how can we deploy these bots on short notice without compromising quality and user privacy?

By Fiete Lüer, September 2020

PDF | HTML | In the Digital Library

The AI revolution

The AI revolution

This article explores the areas of bias in natural language processing, from the tools that are used to analyze the data to the fundamental theories in the field. It delves deeper into the very idea that the data that is analyzed (language) itself shapes human perception of reality, and evolves over time.

By Talia Kohen, April 2019

PDF | HTML | In the Digital Library

Sorry kids, Iron Man's superpowers aren't unique

DEPARTMENT: Hello World

Sorry kids, Iron Man's superpowers aren't unique

By Lara Zupan, Marinka Zitnik, November 2015

PDF | HTML | In the Digital Library

New directions in language processing

COLUMN: INIT

New directions in language processing

By Adrian Scoică, Daniel Bauer, October 2014

PDF | HTML | In the Digital Library

Technology for talking

DEPARTMENT: Milestones

Technology for talking

By Jay Patel, October 2014

PDF | HTML | In the Digital Library

Talking to computers in natural language

SECTION: Features

Talking to computers in natural language

Natural language understanding is as old as computing itself, but recent advances in machine learning and the rising demand of natural-language interfaces make it a promising time to once again tackle the long-standing challenge.

By Percy Liang, October 2014

PDF | HTML | In the Digital Library

To err is human, to correct is divine

To err is human, to correct is divine

Technology has made language learning a more interactive and enjoyable experience, but it has never been smart enough to replace human tutors. However, the latest advances in automated grammatical error correction open up new horizons. Could software ever replace our language teachers?

By Mariano Felice, Zheng Yuan, October 2014

PDF | HTML | In the Digital Library

From wax tablets to touchscreens

From wax tablets to touchscreens

How we can enable users to transmit text to mobile and ubiquitous computer systems as quickly and as accurately as possible.

By Per Ola Kristensson, October 2014

PDF | HTML | In the Digital Library

Ancient Sumerian online

Ancient Sumerian online

Far from its beginnings as symbols pressed into clay tablets, Ancient Sumerian is now being digitized and shared through cutting edge semantic web technologies.

By Terhi Nurmikko-Fuller, October 2014

PDF | HTML | In the Digital Library

Detecting influencers in social media discussions

Detecting influencers in social media discussions

Knowing who's influential can help when planning political campaigns, advertising strategies, or even combating terrorism; and now research into influence detection promises to automate such detection.

By Sara Rosenthal, October 2014

PDF | HTML | In the Digital Library

Spoken dialogue systems

Spoken dialogue systems

Wouldn't it be great if we could simply talk to our technical devices instead of relying on cumbersome displays and keyboards to convey what we want?

By Pierre Lison, Raveesh Meena, October 2014

PDF | HTML | In the Digital Library

A hybrid system for code switch point detection in informal Arabic text

A hybrid system for code switch point detection in informal Arabic text

How to detect the switch between a standard and a dialectal form of a language in written text and why this is important for natural language processing tasks.

By Heba Elfardy, Mohamed Al-Badrashiny, Mona Diab, October 2014

PDF | HTML | In the Digital Library

Miriam Plieninger on language learning with Babbel

Miriam Plieninger on language learning with Babbel

Babbel's Director of Didactics, Miriam Plieninger, weighs in on how mobile apps are rapidly changing the way we approach language learning.

By Daniel Bauer, Billy Rathje, October 2014

PDF | HTML | In the Digital Library

National Centre for Text Mining (NaCTeM)

DEPARTMENT: Labz

National Centre for Text Mining (NaCTeM)

By Georgios Kontonatsios, Matt Shardlow, October 2014

PDF | HTML | In the Digital Library

Scientific computing

COLUMN: INIT

Scientific computing

By Nick Knight, Jack Poulson, March 2013

PDF | HTML | In the Digital Library

Linguistic structure prediction with the sparseptron

SECTION: Features

Linguistic structure prediction with the sparseptron

Recent advances in natural language processing bring together rich representations and scalable machine learning algorithms.

By Noah A. Smith, André F. T. Martins, March 2013

PDF | HTML | In the Digital Library

Designing good MapReduce algorithms

Designing good MapReduce algorithms

An introduction to designing algorithms for the MapReduce framework for parallel processing of big data.

By Jeffrey D. Ullman, September 2012

PDF | HTML | In the Digital Library

Profile Jeff Dean<br />Big data at Google

Profile Jeff Dean
Big data at Google

By Edward Z. Yang, Robert J. Simmons, September 2012

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Introduction

By Justin Solomon, December 2008

PDF | HTML | In the Digital Library

Towards a user-friendly semantic formalism for natural language generation

Computational semantics has become an interesting and important branch of computational linguistics. Born from the fusion of formal semantics and computer science, it is concerned with the automated processing of meaning associated with natural language expressions [2]. Systems of semantic representation, hereafter referred to as semantic formalisms, exist to describe meaning underlying natural language expressions. To date, several formalisms have been defined by researchers from a number of diverse disciplines including philosophy, logic, psychology and linguistics. These formalisms have a number of different applications in the realm of computer science. For example, in machine translation a sentence could be parsed and translated into a series of semantic expressions, which could then be used to generate an utterance with the same meaning in a different language [14]. This paper presents two existing formalisms and examines their user-friendliness. Additionally, a new form of semantic representation is proposed with wide coverage and user-friendliness suitable for a computational linguist.

By Craig Thomas, December 2008

PDF | HTML | In the Digital Library

An approach for detecting prosodic phrase boundaries in spoken english

Prosodic phrasing is the means by which speakers of any given language break up an utterance into meaningful chunks. The term "prosody" itself refers to the tune or intonation of an utterance, and therefore prosodic phrases literally signal the end of one tune and the beginning of another. This study uses phrase break annotations in the Aix-MARSEC corpus of spoken English as a "gold standard" for measuring the degree of correspondence between prosodic phrases and the discrete syntactic grouping of prepositional phrases, where the latter is defined via a chunk parsing rule using nltk_lite's regular expression chunk parser.

A three-way comparison is also introduced between the "gold standard" chunk parsing rule and human judgment in the form of intuitive predictions about phrasing. Results show that even with a discrete syntactic grouping and a small sample of text, problems may arise for this rule-based method due to uncategorical behavior in parts of speech. Lack of correspondence between intuitive prosodic phrases and corpus annotations highlights the optional nature of certain boundary types. Finally, there are clear indications, supported by corpus annotations, that significant prosodic phrase boundaries occur within sentences and not just at full stops.

By Claire Brierley, Eric Atwell, December 2007

PDF | HTML | In the Digital Library

Introduction

By William Stevenson, October 2005

PDF | HTML | In the Digital Library

Using perception in managing unstructured documents

By Ching Kang Cheng, Xiaoshan Pan, October 2005

PDF | HTML | In the Digital Library

Using perception in managing unstructured documents

By Ching Kang Cheng, Xiaoshan Pan, December 2003

PDF | HTML | In the Digital Library