Papers › Evaluating Lexicon Incorporation for Depression Symptom Estimation
Evaluating Lexicon Incorporation for Depression Symptom Estimation
Kirill Milintsevich, Gaël Dias, Kairit Sirts
This paper explores the impact of incorporating sentiment, emotion, and domain-specific lexicons into a transformer-based model for depression symptom estimation. Lexicon information is added by marking the words in the input transcripts of patient-therapist conversations as well as in social media posts. Overall results show that the introduction of external knowledge within pre-trained language models can be beneficial for prediction performance, while different lexicons show distinct behaviours depending on the targeted task. Additionally, new state-of-the-art results are obtained for the estimation of depression level over patient-therapist interviews.
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