mlsanityData to 14 Oct 2026

SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning

arXiv 2208.13077 ↗First posted 27 Aug 2022cs.CL cs.AI cs.HCcited by 8

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Abstract (arXiv)

We propose a recommendation system that suggests treatment strategies to a therapist during the psychotherapy session in real-time. Our system uses a turn-level rating mechanism that predicts the therapeutic outcome by computing a similarity score between the deep embedding of a scoring inventory, and the current sentence that the patient is speaking. The system automatically transcribes a continuous audio stream and separates it into turns of the patient and of the therapist and perform real-time inference of their therapeutic working alliance. The dialogue pairs along with their computed working alliance as ratings are then fed into a deep reinforcement learning recommendation system where the sessions are treated as users and the topics are treated as items. Other than evaluating the empirical advantages of the core components on an existing dataset of psychotherapy sessions, we demonstrate the effectiveness of this system in a web app.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 25 of its 73 references that are in the map. First posted on arXiv 27 Aug 2022.

Builds on

25 of 73 references.

References · 25

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2015Continuous control with deep reinforcement learningcited by 3,407
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13 more
  1. 2019Topic Modeling with Wasserstein Autoencoderscited by 53
  2. 2018Evaluation of Session-based Recommendation Algorithmscited by 37
  3. 2020Neural Topic Modeling with Bidirectional Adversarial Trainingcited by 29
  4. 2013Exploration in Interactive Personalized Music Recommendation: A Reinforcement Learning Approachcited by 22
  5. 2022Deep Annotation of Therapeutic Working Alliance in Psychotherapycited by 14
  6. 2019A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatrycited by 13
  7. 2022Neural Topic Modeling of Psychotherapy Sessionscited by 13
  8. 2020Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RLcited by 11
  9. 2020Predicting human decision making in psychological tasks with recurrent neural networkscited by 11
  10. 2019Split Q Learning: Reinforcement Learning with Two-Stream Rewardscited by 8
  11. 2020Speaker Diarization as a Fully Online Learning Problem in MiniVoxcited by 7
  12. 2022Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlookcited by 7
  13. 2020Online Semi-Supervised Learning in Contextual Bandits with Episodic Rewardcited by 5

Built on by

Cited by year

Citing papers per year: 2022: 3; 2023: 5.

8 papers.

  1. 2023Towards Healthy AI: Large Language Models Need Therapists Toocited by 13
  2. 2023A Survey on Compositional Generalization in Applicationscited by 12
  3. 2022Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlookcited by 10
  4. 2022Working Alliance Transformer for Psychotherapy Dialogue Classificationcited by 9
  5. 2023Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamicscited by 6
  6. 2022Computational Inference in Cognitive Science: Operational, Societal and Ethical Considerationscited by 4
  7. 2023Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosiscited by 4
  8. 2023TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Artscited by 3