Home / Current Issue / Paper 1712895
Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization
Subject area: Science,Engineering and Technology · Area of research: Artificial intelligence
Abstract
Psychotherapy sessions generate large volumes of unstructured conversational data that must be documented, analyzed, and reviewed by therapists. Manual transcription and subjective interpretation of emotional cues are time-consuming and cognitively demanding. This paper presents Inner Me, an AI-assisted framework designed to support psychotherapists through automated speech-to-text transcription, emotion recognition, session summarization, and interactive question?answering.
Keywords
Artificial Intelligence, Psychotherapy, Speech-to-Text, Emotion Recognition, Natural Language Processing
How to cite this paper
Pooja Patil, Prof. Shendage "Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 1256-1256 https://doi.org/10.64388/IREV9I6-1712895
Pooja Patil, Prof. Shendage "Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization" Iconic Research And Engineering Journals, vol. 9, no. 6, Dec. 2025, doi: https://doi.org/10.64388/IREV9I6-1712895
Pooja Patil, Prof. Shendage (2025). Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization. Iconic Research And Engineering Journals, 9(6). doi: https://doi.org/10.64388/IREV9I6-1712895
Pooja Patil, Prof. Shendage "Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization" Iconic Research And Engineering Journals, vol. 9, no. 6, Dec. 2025. Crossref, https://doi.org/10.64388/IREV9I6-1712895
@article{1712895,
author = {Pooja Patil, Prof. Shendage},
title = {Inner Me: An AI-Assisted Framework for Automated Psychotherapy Session Transcription, Emotion Analysis, and Summarization},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {6},
pages = {1256-1256},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712895.pdf},
abstract = {Psychotherapy sessions generate large volumes of unstructured conversational data that must be documented, analyzed, and reviewed by therapists. Manual transcription and subjective interpretation of emotional cues are time-consuming and cognitively demanding. This paper presents Inner Me, an AI-assisted framework designed to support psychotherapists through automated speech-to-text transcription, emotion recognition, session summarization, and interactive question?answering.},
keywords = {Artificial Intelligence, Psychotherapy, Speech-to-Text, Emotion Recognition, Natural Language Processing},
month = {December},
doi = {https://doi.org/10.64388/IREV9I6-1712895}
}