There is a recognised need for more research on the topic of emotion recognition from speech, and clear and defined methodology in this area is still lacking. Most studies in the field of emotional speech recognition and ...

Wikipedia is a great source of knowledge, but due to its open-collaboration nature, it presents some limitations. Namely, the uneven distribution of content, the low overlap in topic coverage, the differences in the ...

Grammatical Error Detection (GED) is a challenging NLP task that has not received a lot of research attention in the recent years, especially in the Swedish language. However, in the world we live in, where there are ...

When building efficient dialogue systems, a major challenge is recovering from miscommunication. Analyzing human-human interaction leads to discovering repair strategies that contribute towards conversational systems ...

In this paper we will attempt to predict and assess the performance of predicting laughter using a BERT model (Devlin et al., 2019), and a BERT model finetuned on the Open subtitles dataset with and without considering ...

Language models are becoming increasingly popular. These models can contain social biases about various groups of people in them. The reproduction of biased beliefs can have harmful impacts on the groups they are about. ...

Affective polarization – the tendency to hold negative attitudes towards an out-group and biased, positive attitudes towards an in-group – is a hot topic in research and public debate. There are concerns that news media’s ...

Neural machine translation is a method used in automatic translation that makes use of artificial neural networks. A single model takes an input sequence and predicts the most likely output sequence of words after being ...

Background: Natural Language Understanding (NLU) is an important component in Dialogue Systems (DS) which makes the utterances of humans understandable by machines. A central aspect of NLU is intent classification. In ...