Lyssn uses machine learning to evaluate psychotherapy sessions and generates performance-based feedback.
Lyssn uses speech recognition to recognize words and sentences. Our technology also detects emotional tone, offering richer cues to help evaluate sessions.
In psychotherapy, there is more than one speaker. Lyssn differentiates between therapists and clients (“who speaks when?”). We partition the transcript into speaker-labeled talk turns for easier analysis.
Lyssn uses state-of-the-art machine learning technology to identify key session content, including specific therapist interventions, discussion topics, and emotions.
Lyssn provides an interactive tool for reviewing and annotating sessions, including high-level session summaries and detailed information contained within session transcripts.
Until now, feedback on the quality of psychotherapy relied on burdening patients with questionnaires, or slow and labor-intensive human evaluations of session recordings. Lyssn utilizes state-of-the-art machine learning technology, trained on thousands of human-evaluated sessions, to process the content of your session in real time.
Lyssn performance-based feedback is designed for therapist's own reflection and growth, training in specific evidence-based practices and skills, and to deepen and facilitate the process of supervision. Lyssn is currently developing technology to provide feedback on the quality and content of psychotherapy to patient's themselves
Learning from your work should be easy. Our designers worked directly with therapists and trainers to develop an easy-to-use, elegant platform so that you not only receive feedback instantly but in a way you can understand.
What clients share with their therapists is private, and we take security seriously. Our infrastructure utilizes two-factor authentication and encrypted, HIPAA-compliant cloud servers.
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Proceedings of the IEEE