---
title: Fluency Benchmark
emoji: 🎙️
colorFrom: blue
colorTo: green
sdk: docker
app_port: 7860
app_file: app.py
pinned: false
---

# Fluency Benchmark App

Upload an English speech audio file to measure temporal fluency — flow, continuity, and pausing behavior.

## What It Measures

- **Temporal fluency** — flow and continuity of speech
- **Pause behavior** — frequency, duration, and placement of pauses
- **Articulation** — smoothness of delivery (legato vs staccato)
- **Hesitation diagnosis** — cognitive load and utterance constraints

**What it does NOT measure:** grammar, vocabulary, pronunciation, or accent.

## Pipeline Stages

1. **VAD** (Silero) — detects speech vs silence, computes 6 temporal features
2. **Transcription** (WhisperX base) — word-level aligned transcript
3. **Placement** — classifies each pause as boundary-aligned or mid-clause
4. **FA Features** — word duration, confidence, filled pauses, speech rate CV
5. **Syntactic** — POS-tags pauses as before content vs function words
6. **Inference** — 6 ordinal models + 1 dominance model → predictions
7. **Composite** — 6 dimensions weighted → percentile + confidence interval

## Output

- **Fluency Percentile** (0-100, relative to benchmark population of 917 speakers)
- **Fluency Band** (LOW / MEDIUM / HIGH)
- **6 Dimension Scores** (Continuity, Pause Quality, Placement, Articulation, Dominance, Word Precision)
- **Ordinal Predictions** (Pause Frequency, Duration, Placement, Cognitive Load, Utterance Constraints, Articulation)
- **95% Confidence Interval** (Dirichlet bootstrap)