no code implementations • LREC 2016 • Akira Hayakawa, Saturnino Luz, Loredana Cerrato, Nick Campbell
The corpus design is inspired by the HCRC Map Task Corpus which was initially designed to support the investigation of linguistic phenomena, and has been the focus of a variety of studies of communicative behaviour.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • LREC 2018 • Volha Petukhova, Andrei Malchanau, Youssef Oualil, Dietrich Klakow, Saturnino Luz, Fasih Haider, Nick Campbell, Dimitris Koryzis, Dimitris Spiliotopoulos, Pierre Albert, Nicklas Linz, Alex, Jan ersson
1 code implementation • 25 Nov 2018 • Saturnino Luz, Sofia de la Fuente, Pierre Albert
We present an approach to automatic detection of Alzheimer's type dementia based on characteristics of spontaneous spoken language dialogue consisting of interviews recorded in natural settings.
no code implementations • 28 Aug 2019 • Fasih Haider, Senja Pollak, Pierre Albert, Saturnino Luz
A machine learning model trained on a smaller feature set will reduce the memory and computational resources of an emotion recognition system which can result in lowering the barriers for use of health monitoring technology.
no code implementations • 3 Nov 2019 • Bridget Kane, Jing Su, Saturnino Luz
While machine learning (ML) systems have produced great advances in several domains, their use in support of complex cooperative work remains a research challenge.
no code implementations • 14 Apr 2020 • Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney
ADReSS provides researchers with a benchmark speech dataset which has been acoustically pre-processed and balanced in terms of age and gender, defining two cognitive assessment tasks, namely: the Alzheimer's speech classification task and the neuropsychological score regression task.
1 code implementation • 12 May 2020 • Blaž Škrlj, Nika Eržen, Shane Sheehan, Saturnino Luz, Marko Robnik-Šikonja, Senja Pollak
Neural language models are becoming the prevailing methodology for the tasks of query answering, text classification, disambiguation, completion and translation.
no code implementations • 12 Oct 2020 • Sofia de la Fuente Garcia, Craig Ritchie, Saturnino Luz
We concluded that the main limitations of the field are poor standardisation, limited comparability of results, and a degree of disconnect between study aims and clinical applications.
no code implementations • 23 Mar 2021 • Saturnino Luz, Fasih Haider, Sofia de la Fuente, Davida Fromm, Brian MacWhinney
Building on the success of the ADReSS Challenge at Interspeech 2020, which attracted the participation of 34 teams from across the world, the ADReSSo Challenge targets three difficult automatic prediction problems of societal and medical relevance, namely: detection of Alzheimer's Dementia, inference of cognitive testing scores, and prediction of cognitive decline.
no code implementations • 14 Jun 2022 • Saturnino Luz
This chapter provides an introduction to computational linguistics methods, with focus on their applications to the practice and study of translation.
no code implementations • 13 Jan 2023 • Saturnino Luz, Fasih Haider, Davida Fromm, Ioulietta Lazarou, Ioannis Kompatsiaris, Brian MacWhinney
This Signal Processing Grand Challenge (SPGC) targets a difficult automatic prediction problem of societal and medical relevance, namely, the detection of Alzheimer's Dementia (AD).
no code implementations • 11 Aug 2023 • Saturnino Luz, Masood Masoodian
The proliferation of consumer health devices such as smart watches, sleep monitors, smart scales, etc, in many countries, has not only led to growing interest in health monitoring, but also to the development of a countless number of ``smart'' applications to support the exploration of such data by members of the general public, sometimes with integration into professional health services.
no code implementations • 23 Sep 2023 • Qingkun Deng, Saturnino Luz, Sofia de la Fuente Garcia
These interpretations allow clinicians to verify the validity of predictions made by depression detection tools, promoting their clinical implementations.
1 code implementation • EACL (Hackashop) 2021 • Blaž Škrlj, Shane Sheehan, Nika Eržen, Marko Robnik-Šikonja, Saturnino Luz, Senja Pollak
Large pretrained language models using the transformer neural network architecture are becoming a dominant methodology for many natural language processing tasks, such as question answering, text classification, word sense disambiguation, text completion and machine translation.
no code implementations • EACL (Hackashop) 2021 • Shane Sheehan, Saturnino Luz, Masood Masoodian
In this paper we present TeMoTopic, a visualization component for temporal exploration of topics in text corpora.