# Neural Topic Modeling of Psychotherapy Sessions

arXiv: https://arxiv.org/abs/2204.10189 · HTML: https://mlsanity.com/paper/2204.10189/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 28 references that are in the map.
- First posted on arXiv 13 Apr 2022.

## Builds on (most cited first, 12 of 12)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [Topic Modeling in Embedding Spaces](https://mlsanity.com/paper/1907.04907/) (2019)
- [Neural Variational Inference for Text Processing](https://mlsanity.com/paper/1511.06038/) (2015)
- [From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbots](https://mlsanity.com/paper/1801.01957/) (2018)
- [Discovering Discrete Latent Topics with Neural Variational Inference](https://mlsanity.com/paper/1706.00359/) (2017)
- [Topic Modeling with Wasserstein Autoencoders](https://mlsanity.com/paper/1907.12374/) (2019)
- [Neural Topic Modeling with Bidirectional Adversarial Training](https://mlsanity.com/paper/2004.12331/) (2020)
- [Deep Annotation of Therapeutic Working Alliance in Psychotherapy](https://mlsanity.com/paper/2204.05522/) (2022)
- [A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry](https://mlsanity.com/paper/1906.11286/) (2019)
- [Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL](https://mlsanity.com/paper/2005.04544/) (2020)
- [Predicting human decision making in psychological tasks with recurrent neural networks](https://mlsanity.com/paper/2010.11413/) (2020)
- [Split Q Learning: Reinforcement Learning with Two-Stream Rewards](https://mlsanity.com/paper/1906.12350/) (2019)

## Built on by (most cited first, 13 of 13)

- [Towards Healthy AI: Large Language Models Need Therapists Too](https://mlsanity.com/paper/2304.00416/) (2023)
- [Reinforcement Learning and Bandits for Speech and Language Processing: Tutorial, Review and Outlook](https://mlsanity.com/paper/2210.13623/) (2022)
- [Working Alliance Transformer for Psychotherapy Dialogue Classification](https://mlsanity.com/paper/2210.15603/) (2022)
- [SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning](https://mlsanity.com/paper/2208.13077/) (2022)
- [COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling](https://mlsanity.com/paper/2402.14701/) (2024)
- [Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlook](https://mlsanity.com/paper/2206.07304/) (2022)
- [Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics](https://mlsanity.com/paper/2303.09601/) (2023)
- [Computational Inference in Cognitive Science: Operational, Societal and Ethical Considerations](https://mlsanity.com/paper/2210.13526/) (2022)
- [Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis](https://mlsanity.com/paper/2306.03902/) (2023)
- [TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts](https://mlsanity.com/paper/2302.10845/) (2023)
- [Fine-Tuning Large Audio-Language Models with LoRA for Precise Temporal Localization of Prolonged Exposure Therapy Elements](https://mlsanity.com/paper/2506.09707/) (2025)
- [Discovering Mental Health Research Topics with Topic Modeling](https://mlsanity.com/paper/2308.13569/) (2023)
- [Word Clouds as Common Voices: LLM-Assisted Visualization of Participant-Weighted Themes in Qualitative Interviews](https://mlsanity.com/paper/2508.07517/) (2025)

## Abstract (arXiv)

In this work, we compare different neural topic modeling methods in learning the topical propensities of different psychiatric conditions from the psychotherapy session transcripts parsed from speech recordings. We also incorporate temporal modeling to put this additional interpretability to action by parsing out topic similarities as a time series in a turn-level resolution. We believe this topic modeling framework can offer interpretable insights for the therapist to optimally decide his or her strategy and improve psychotherapy effectiveness.