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Found 7 papers, 0 papers with code
Optimizing Contextual Speech Recognition Using Vector Quantization for Efficient Retrieval
However, the biasing mechanism is typically based on a cross-attention module between the audio and a catalogue of biasing entries, which means computational complexity can pose severe practical limitations on the size of the biasing catalogue and consequently on accuracy improvements.
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.
Multimodal Clustering with Role Induced Constraints for Speaker Diarization
Speaker clustering is an essential step in conventional speaker diarization systems and is typically addressed as an audio-only speech processing task.
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.
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.
