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Detta blogginlägg är en uppföljning av ett tidigare som inleds med en beskrivning av en data-intensiv forskningsmetodologi, börja gärna med den.

This blog is a piece of opinion where I sketch the process of developing NLP-based applications for second language learning and look at the process from the point of view of typical (mis)conceptions and challenges, as I have experienced them. Are we over-trusting the potential of NLP?

I en värld där AI tar en allt större plats har datadriven forskning blivit orden på allas läppar. I det här blogginlägget tänkte jag prata lite om vad det innebär att forska med hjälp av stora mängder textdata, primärt inom humaniora.

Shafqat Mumtaz Virk, Harald Hammarström, Markus Forsberg, Søren Wichmann

Zipfs lag, uppkallad efter den amerikanske lingvisten George Kingsley Zipf, säger att ett ords frekvens är omvänt proportionellt mot dess plats i en frekvenslista. Vad innebär det?

A comment often received by the reviewers of manuscripts to scientific conferences and journals is one about the representative sample under scrutiny and whether there are any solid arguments for accepting that the population characteristics, and particularly the features extracted from the empir

Recently, we have seen a surge of methods that claim to embed meaning from textual corpora. But is that possible? Can text really reveal meaning, and if so, can current NLP methods detect it? Can our methods, as they some times claim, understand?

What if you could find all arguments in a text without having to read it? Or, what if you could search a database for a controversial topic and immediately get arguments for and against it, gathered from text all around the internet?

Continuing on last month's theme on Swedish parliamentary data, we would like to introduce a new tool designed to use and explore them.

The Swedish Parliament (Riksdagen) continuously releases open data on its website, which includes documents approved and used during parliamentary sessions as well as what each member of parliament votes during each roll call (voting session).

In recent years, neural network based approaches (i.e. deep learning) have been the main models for state-of-the-art systems in natural language processing, whether that is in machine translation, natural language inference, language modeling or sentiment analysis.

In our research group, we are exploring ways of analysing language to find early signs of possible cognitive impairment, which may develop to dementia.

Ord kan förändra sina betydelser. Man behöver inte en doktorgrad i språkvetenskap för att upptäcka att grym i (1) betyder inte samma sak som i (2).

At Språkbanken we collect resources, mainly lexica and corpora, most of them in Swedish. So far we have collected Swedish corpora totalling 13 billions of words, in all kinds of genres and from all time periods.

Among the flurry of Språkbanken’s historical resources we find the Kubhist corpus – a diachronic collection of historical newspaper texts – in two versions: Kubhist 1 spanning the time period of 1750–1950, and Kubhist 2 spanning the time period of 1645–1926.

One of the most central aspects of language learning is the learning of words.

Ordet tsunami var helt okänt för de flesta i Sverige före julhelgen 2004. Då inträffade ju det som så småningom kom att kallas tsunamikatastrofen, en förfärlig naturkatastrof som skördade otaliga dödsoffer i Sydasien och Sydostasien.