Poverty of Content of Speech

What problem does it solve?

This Skill helps researchers and clinicians automatically classify speech fragments as Poverty of Content of Speech (POCS) or No Poverty of Content of Speech (NO-POCS), enabling consistent analysis of language thought disorders.

Core Features & Use Cases

• Text-based classification: labels each fragment as POCS or NO-POCS with optional rationale.
• Batch processing: accepts multiple fragments in a single run for research datasets.
• Use Case: analyze transcripts from clinical interviews to identify fragments that show verbose yet content-poor speech patterns.

Quick Start

Provide one or more text fragments to be labeled. Example: "I spent the day thinking about relationships, but I can't explain why I feel uncertain." The skill returns a per-fragment label.