Evaluating Lexicon Incorporation for Depression Symptom Estimation
<|reference_start|>Evaluating Lexicon Incorporation for Depression Symptom Estimation: 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.<|reference_end|>
@article{milintsevich2024evaluating,
    title={Evaluating Lexicon Incorporation for Depression Symptom Estimation},
    author={Kirill Milintsevich, Ga"el Dias and Kairit Sirts},
    journal={arXiv preprint arXiv:2404.19359},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.19359},
    primaryClass={cs.CL cs.AI}
}