Decode Speech Emotion via Acoustic Intelligence
VoxSentix AI leverages parallel machine learning pipelines to analyze vocal tract dynamics and spectral frequencies. Map human emotion instantly from high-dimensional statistical signal vectors across diverse language frameworks.
Dynamic Waveform Capture
Record live acoustic signals straight from your hardware. Our visualizer processes incoming stream amplitude boundaries immediately.
Cross-Lingual Resonance
By extracting pure physical attributes (pitch, amplitude, spectral envelope), our system translates emotional states regardless of accent or language.
Fused Majority Voting
Combines tree-based decision surfaces using a soft-voting classifier to generate highly balanced, class-calibrated probabilities.
Acoustic stream idle. Tap button to record sound wave.
Upload Audio File
Drag audio file here or click to import local `.wav` or `.mp3` format
Classifier Specifications
F1-Score Calibration
Evaluated on standard RAVDESS Speech test subsets, verifying robust ensemble performance.
Pipeline Processing Mechanics
Signal Mapping
Raw audio streams are decomposed into 728 statistical boundaries mapping spectral envelope and pitch classes.
Dynamic Standardizing
Vectors undergo standard scaling to normalize speaker volume levels and attenuate environmental noise.
Ensemble Evaluation
Three specialized machine learning algorithms inspect the scaled data vectors across independent paths.
Synthesized Voting
Soft probability scores are aggregated to output a class-calibrated prediction with detailed confidence weights.
Developer Portal
Connect with Muhammad Shahbaz for integration support, API collaborations, or project questions.