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Found 8 papers, 0 papers with code
Leveraging Task Transferability to Meta-learning for Clinical Section Classification with Limited Data
Leveraging the NNCE, we develop strategies for selecting clinical categories and sections from source task data to boost cross-domain meta-learning accuracy.
Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios
In psychotherapy interactions, the quality of a session is assessed by codifying the communicative behaviors of participants during the conversation through manual observation and annotation.
An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates
In particular, we model the global quality as a linear function of the local quality scores, which allows us to update the segment-level quality estimates based on the session-level quality prediction.
Automated Quality Assessment of Cognitive Behavioral Therapy Sessions Through Highly Contextualized Language Representations
In this work, we propose a BERT-based model for automatic behavioral scoring of a specific type of psychotherapy, called Cognitive Behavioral Therapy (CBT), where prior work is limited to frequency-based language features and/or short text excerpts which do not capture the unique elements involved in a spontaneous long conversational interaction.
Automated Evaluation Of Psychotherapy Skills Using Speech And Language Technologies
With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services.
Towards end-2-end learning for predicting behavior codes from spoken utterances in psychotherapy conversations
Spoken language understanding tasks usually rely on pipelines involving complex processing blocks such as voice activity detection, speaker diarization and Automatic speech recognition (ASR).
Feature Fusion Strategies for End-to-End Evaluation of Cognitive Behavior Therapy Sessions
We propose a novel method to augment the word-based features with the utterance level tags for subsequent CBT code estimation.
A Label Proportions Estimation Technique for Adversarial Domain Adaptation in Text Classification
The DAN-LPE simultaneously trains a domain adversarial net and processes label proportions estimation by the confusion of the source domain and the predictions of the target domain.
