by
Michael A. Covington;
S. L. Anya Lunden;
Sarah L. Cristofaro;
Claire R. Wan;
C. Thomas Bailey;
Beth Broussard;
Robert Fogarty;
Stephanie Brown-Johnson;
Shayi Zhang;
Michael T. Compton
Background: Aprosody, or flattened speech intonation, is a recognized negative symptom of schizophrenia, though it has rarely been studied from a linguistic/phonological perspective. To bring the latest advances in computational linguistics to the phenomenology of schizophrenia and related psychotic disorders, a clinical first-episode psychosis research team joined with a phonetics/computational linguistics team to conduct a preliminary, proof-of-concept study. Methods: Video recordings from a semi-structured clinical research interview were available from 47 first-episode psychosis patients. Audio tracks of the video recordings were extracted, and after review of quality, 25 recordings were available for phonetic analysis. These files were de-noised and a trained phonologist extracted a 1-minute sample of each patient's speech. WaveSurfer 1.8.5 was used to create, from each speech sample, a file of formant values (F0, F1, F2, where F0 is the fundamental frequency and F1 and F2 are resonance bands indicating the moment-by-moment shape of the oral cavity). Variability in these phonetic indices was correlated with severity of Positive and Negative Syndrome Scale negative symptom scores using Pearson correlations. Results: A measure of variability of tongue front-to-back position-the standard deviation of F2-was statistically significantly correlated with the severity of negative symptoms (r= - 0.446, p=0.03). Conclusion: This study demonstrates a statistically significant and meaningful correlation between negative symptom severity and phonetically measured reductions in tongue movements during speech in a sample of first-episode patients just initiating treatment. Further studies of negative symptoms, applying computational linguistics methods, are warranted.
In this data article, we present to the data science, natural language processing and public heath communities an unlabeled corpus and a set of language models. We collected the data from Twitter using drug names as keywords, including their common misspelled forms. Using this data, which is rich in drug-related chatter, we developed language models to aid the development of data mining tools and methods in this domain. We generated several models that capture (i) distributed word representations and (ii) probabilities of n-gram sequences. The data set we are releasing consists of 267,215 Twitter posts made during the four-month period—November, 2014 to February, 2015. The posts mention over 250 drug-related keywords. The language models encapsulate semantic and sequential properties of the texts.
This investigation examined two controversies in the autobiographical literature: how cross-language immigration affects the distribution of autobiographical memories across the lifespan and under what circumstances language-dependent recall is observed. Both Spanish/English bilingual immigrants and English monolingual non-immigrants participated in a cue word study, with the bilingual sample taking part in a within-subject language manipulation. The expected bump in the number of memories from early life was observed for non-immigrants but not immigrants, who reported more memories for events surrounding immigration. Aspects of the methodology addressed possible reasons for past discrepant findings. Language-dependent recall was influenced by second-language proficiency. Results were interpreted as evidence that bilinguals with high second-language proficiency, in contrast to those with lower second-language proficiency, access a single conceptual store through either language. The final multi-level model predicting language-dependent recall, including second-language proficiency, age of immigration, internal language, and cue word language, explained ¾ of the between-person variance and 1 / 5 of the within-person variance. We arrive at two conclusions. First, major life transitions influence the distribution of memories. Second, concept representation across multiple languages follows a developmental model. In addition, the results underscore the importance of considering language experience in research involving memory reports.