Checking in on grammar checking

‘Checking in on Grammar Checking’ by Robert Dale is the latest Industry Watch column to be published in the journal Natural Language Engineering.

Reflecting back to 2004, industry expert Robert Dale reminds us of a time when Microsoft Word was the dominant software used for grammar checking. Bringing us up-to-date in 2016, Dale discusses the evolution, capabilities and current marketplace for grammar checking and its diverse range of users: from academics, men on dating websites to the fifty top celebrities on Twitter.

Below is an extract from the article, which is available to read in full here.

An appropriate time to reflect
I am writing this piece on a very special day. It’s National Grammar Day, ‘observed’ (to . . . → Read More: Checking in on grammar checking

How to make money in Machine Translation

Machine Translation across the world

Extract from the article ‘How to make money in the translation business’ by industry expert Robert Dale published in the journal Natural Language Engineering.

An anniversary year

2016 marks the fiftieth anniversary of an important event in the history of Machine Translation (MT). In 1966, after two years of work, the group of seven scientists who constituted the US National Science Foundation’s Automatic Language Processing Advisory Committee (ALPAC) handed down a 124-page report that was, well, somewhat negative about the state of MT research and its prospects. The ALPAC report is widely credited with causing the US government to drastically reduce funding in MT, and other countries to follow suit. . . . → Read More: How to make money in Machine Translation

Machine learning helps computers predict near-synonyms

Choosing the best word or phrase for a given context from among candidate near-synonyms, such as “slim” and “skinny”, is something that human writers, given some experience, do naturally; but for choices with this level of granularity, it can be a difficult selection problem for computers.

Researchers from Macquarie University in Australia have published an article in the journal Natural Language Engineering, investigating whether they could use machine learning to re-predict a particular choice among near-synonyms made by a human author – a task known as the lexical gap problem.

They used a supervised machine learning approach to this problem in which the weights of different features of a document are learned computationally. Through using this approach, the computers were able to predict . . . → Read More: Machine learning helps computers predict near-synonyms

Can your phone make you laugh?

Funny Texting

Examples of humorous and sometimes awkward autocorrect substitutions happen all the time. Typing ‘funny autocorrect’ into Google brings up page upon page of examples where phones seem to have a mind of their own.

A group of researchers at the University of Helsinki, under the lead of Professor Hannu Toivonen, have been examining word substitution and sentence formation, to see the extent to which they can implement a completely automatic form of humour generation. The results have been published online in the in the journal Natural Language Engineering.

Basing the experiment on the ideas and methods of computational humour explored by Alessandro Valitutti for several years, the researchers worked with short length text messages changing one word to another one, turning . . . → Read More: Can your phone make you laugh?