Raw Audio Cues: How Behavioral Analysis Works
Raw Audio Cues is auraScribe's exhaustive chronological log of observable behavioral signals captured directly from meeting audio. It is the foundation of everything that makes auraScribe different from a transcription tool.
What Raw Audio Cues captures
During the second pass of the 3-pass pipeline, auraScribe's AI listens to the audio alongside the transcript and logs every observable behavioral signal:
- Vocal patterns: Tone shifts, pace changes, volume variations, vocal fry, breathiness
- Conversational signals: Hesitations, filler words, self-corrections, trailing off
- Interaction dynamics: Interruptions, overlapping speech, back-channeling, silence
- Engagement markers: Laughter, audible agreement/disagreement, enthusiasm shifts
- Power dynamics: Who sets the agenda, who defers, who redirects, who is sidelined
- Temporal patterns: Energy changes across the meeting, attention drops, re-engagement moments
Observable behaviors, not emotions
A critical distinction: auraScribe analyses observable behaviors, not emotions. It will note that "Speaker 2's pace increased and pitch rose during the pricing discussion" — an objective observation. It will not claim that "Speaker 2 was anxious about pricing" — an emotional inference.
This distinction is not just philosophical. The EU AI Act (Article 50 and related provisions) restricts emotion recognition systems. auraScribe is designed from the ground up to work within these boundaries, using a compliance engine that automatically rewrites any analysis that crosses from observable behavior into emotional attribution.
Why this matters
Transcripts capture words. Raw Audio Cues capture everything else. A meeting where everyone "agreed" on the surface may show hesitation, disengagement, or passive resistance in the audio signals. A negotiation that seemed routine may reveal power shifts that only become obvious in hindsight.
By surfacing these signals objectively, auraScribe gives professionals the self-awareness to prepare better, communicate sharper, and understand what really happened in every conversation.
How it feeds the analysis
Raw Audio Cues are not just a log — they are the primary input for Pass 3's behavioral summary and per-speaker remarks. The AI reads the transcript alongside the cues to produce:
- A behavioral summary of group dynamics (10-15 bullet points)
- Per-speaker individual remarks with coaching points (5-8 sentences each)
- Buyer intent signals when commercial patterns are detected
Without Raw Audio Cues, these outputs would be generic summaries based on words alone — essentially what every other transcription tool produces.