ArticleInterspeech2018
Using Prosodic and Lexical Information for Learning Utterance-level Behaviors in Psychotherapy.
Article in Interspeech, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Natural language processing for mental health interventions: a systematic review and research framework.Translational psychiatry · 2023Pooled it
- Association of machine-learning-rated supportive counseling skills with psychotherapy outcome.Journal of consulting and clinical psychology · 2025Article
- Clinical Questions and Psychological Change: How Can Artificial Intelligence Support Mental Health Practitioners?Behavioral sciences (Basel, Switzerland) · 2024Article
- An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates.Computer speech & language · 2022Article
- Automated evaluation of psychotherapy skills using speech and language technologies.Behavior research methods · 2022Article
- Automated quality assessment of cognitive behavioral therapy sessions through highly contextualized language representations.PloS one · 2021Article
- Multimodal Automatic Coding of Client Behavior in Motivational Interviewing.Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference) · 2020Article
- Towards End-2-end Learning for Predicting Behavior Codes from Spoken Utterances in Psychotherapy Conversations.Proceedings of the conference. Association for Computational Linguistics. Meeting · 2020Article
- IMPROVING THE PREDICTION OF THERAPIST BEHAVIORS IN ADDICTION COUNSELING BY EXPLOITING CLASS CONFUSIONS.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2019Article
- Multi-label Multi-task Deep Learning for Behavioral Coding.IEEE transactions on affective computingArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In this paper, we present an approach for predicting utterance level behaviors in psychotherapy sessions using both speech and lexical features. We train long short term memory (LSTM) networks with an attention mechanism using words, both manually and automatically transcribed, and prosodic features, at the word level, to predict the annotated behaviors. We demonstrate that prosodic features provide discriminative information relevant to the behavior task and show that they improve prediction when fused with automatically derived lexical features. Additionally, we investigate the weights of the attention mechanism to determine words and prosodic patterns which are of importance to the behavior prediction task.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.