SPEAKapp – Remote monitoring of language production to predict cognitive functioning

Authors

  • Chiara Di San Pietro Ab.Acus s.r.l., Milan, Italy Author
  • Valentina Simonetti Ab.Acus s.r.l., Milan, Italy Author
  • Cristina Crocamo Department of Medicine and Surgery, University of Milano-Bicocca, Italy Author
  • Maria Bulgheroni Ab.Acus s.r.l., Milan, Italy Author

DOI:

https://doi.org/10.36505/ExLing-2021/12/0009/000482

Keywords:

language, NLP, mobile app, DSM, neuropsychology

Abstract

Language production and comprehension can provide a useful perspective into an individual's mental health and cognitive abilities. SPEAKapp is a mobile application designed to deliver and analyze speech and language data for clinical and research purposes. It implements pre- and post-processing techniques based on Natural Language Processing (NLP) and Distributional Semantic Models (DSM) of language. The first functional prototype was tested for accuracy of data acquisition and elaboration, as well as for usability and acceptability in a pilot sample of fragile users. SPEAKapp showed good accuracy and replicability of results, and participants felt comfortable using the application. Further developments of the application are presented.

References

Barattieri di San Pietro, C., de Girolamo, G. C., Luzzatti, C., & Marelli, M. (2020). Mind your models! Distributional semantic models for the analysis of verbal fluency tasks in schizophrenia spectrum disorders. The 26th Architectures and Mechanisms for Language Processing Conference (virtual congress).

Boersma, P., & Weenink, D. (2021). Praat: Doing phonetics by computer [Computer program]. http://www.praat.org/

Brooke, J. (1996). SUS-A quick and dirty usability scale. Usability Evaluation in Industry, 189(194), 4-7.

Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104(2), 211.

Mandera, P., Keuleers, E., & Brysbaert, M. (2017). Explaining human performance in psycholinguistic tasks with models of semantic similarity based on prediction and counting: A review and empirical validation. Journal of Memory and Language, 92, 57-78.

Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.

Troyer, K., Moscovitch, M., & Winocur, G. (1997). Clustering and switching as two components of verbal fluency: Evidence from younger and older healthy adults. Neuropsychology, 11(1), 138-146.

Downloads

Published

01-01-2021

How to Cite

SPEAKapp – Remote monitoring of language production to predict cognitive functioning. (2021). Linguistic Proceedings Series, 12(1), 33-36. https://doi.org/10.36505/ExLing-2021/12/0009/000482

Similar Articles

11-20 of 292

You may also start an advanced similarity search for this article.