Advanced psychological state estimator analyzes voice patterns, stress indicators, cognitive load, and mental focus levels for wellness and performance monitoring.
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Psychological State Estimator is an advanced AI-powered tool that analyzes voice patterns, stress indicators, cognitive load, and mental focus levels for wellness and performance monitoring. It examines psychological indicators in voice and speech patterns, listening for signs of psychological states such as stress levels, cognitive load, mental focus, emotional regulation, and overall psychological balance. The tool analyzes speech and vocal patterns that might indicate psychological states, providing observations about stress, cognitive load, focus, and emotional regulation. Important note: This is not clinical analysis but observation of speech and vocal patterns that might indicate psychological states, avoiding specific diagnostic claims. This makes it valuable for wellness monitoring, performance assessment, stress management, or anyone interested in understanding psychological indicators in voice.
Upload your voice sample and the AI analyzes psychological indicators systematically. It examines stress indicators including vocal tension, speech rate changes, and other stress markers. Cognitive load analysis looks for signs of mental effort or cognitive strain. Mental focus assessment evaluates concentration and attention levels. Emotional regulation evaluation examines how emotions are managed. Overall psychological balance assessment considers multiple indicators together. The tool provides detailed analysis of these indicators, noting patterns that might suggest psychological states, explaining what indicates different states, and offering observations about psychological well-being. It emphasizes that this is observational analysis, not clinical diagnosis, and avoids making specific diagnostic claims. You can provide context about the speaker's situation in the notes field to help refine analysis.
Categorize content by main topics and subtopics. Identifies primary subject, themes, and specific points discussed. Creates a hierarchical topic map with timing.
Create concise summaries of audio content. Identifies main points, arguments, facts, and takeaways. Provides brief executive and detailed topic-based summaries.
Create descriptions of non-speech audio elements. Identifies background sounds, music, effects. Provides accessibility-focused descriptions for context.
Simplify complex spoken language for clearer understanding. Identifies jargon and technical terms, providing plain language explanations while maintaining core meaning.
Identify and label different languages in mixed audio. Notes language switches, estimates non-English content, and maps language use throughout the audio.
Check if spoken words match emotional tone. Identifies potential sarcasm, irony, hidden emotions, or inauthentic expressions. Analyzes verbal/vocal alignment.