Bio-Acoustic Voice Analysis Technology

Every human voice carries a unique bio-acoustic fingerprint shaped by physiology, emotion, and cognitive state. ORAVYS captures this fingerprint through hundreds of acoustic features extracted per audio frame and processed by 110+ specialized engines.

What Is Bio-Acoustic Analysis?

Bio-acoustic analysis is the science of extracting biological information from sound signals produced by living organisms. In the context of voice, this means analyzing the physical properties of speech that reflect the speaker's vocal tract anatomy, respiratory patterns, laryngeal muscle tension, and neurological control. Unlike simple speech recognition, which focuses on what is said, bio-acoustic analysis examines how something is said at a level far beyond conscious control.

Comprehensive Features Per Frame

ORAVYS extracts a comprehensive feature vector from every analysis frame:

MFCC Coefficients + Deltas

Mel-Frequency Cepstral Coefficients plus first and second-order derivatives capture spectral envelope dynamics and vocal tract shape.

Spectral Descriptors

Centroid, bandwidth, rolloff, and flatness quantify the frequency distribution and timbral qualities of each frame.

12 Chroma Features

Pitch class distributions reveal harmonic structure and tonal patterns independent of octave.

Energy & Zero-Crossing

RMS energy and zero-crossing rate measure amplitude dynamics and the balance between voiced and unvoiced segments.

Harmonic-to-Noise Ratio

HNR quantifies voice quality by measuring the proportion of harmonic energy to noise, reflecting vocal fold health and control.

Formant Tracking

Resonant frequency trajectories trace articulatory movements and detect micro-variations invisible to human listeners.

Engine Categories

The 178 engines in the ORAVYS platform are organized into specialized categories, each targeting a different dimension of the voice signal:

From Raw Audio to Actionable Insight

When audio enters ORAVYS, it passes through a multi-stage pipeline. First, the signal is preprocessed: resampled to 22,050 Hz, normalized, and optionally voice-isolated to remove background noise. Next, the high-dimensional feature vector is extracted frame-by-frame. These features are then routed to all applicable engines in parallel using a dependency-aware executor that handles engine prerequisites and graceful degradation.

Each engine returns a structured result with a confidence score, anomaly flags, and detailed metrics. A meta-analysis layer aggregates these results into a coherent voice authenticity profile. The final output includes overall authenticity scores, per-engine breakdowns, and flagged incongruence patterns -- all with full transparency about how conclusions were reached.

Experience Bio-Acoustic Analysis

Record or upload a voice sample to see 178 engines dissect the bio-acoustic signal in real time.

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