BurstInjector™
Sentence-Length Variance for Natural Reading Rhythm
BurstInjector™ analyzes and corrects the unnatural sentence-length variance signature of AI-generated text. LLMs produce text where sentence lengths are suspiciously uniform — human writers naturally alternate short punchy statements with longer analytical sentences. BurstInjector™ identifies this regularity and reshapes paragraph rhythm to match real human writing distributions.
How It Works
Variance Signature Analysis
Measures sentence-length coefficient of variation (CV) across the input. AI text typically shows CV < 0.35; human writing averages CV 0.55–0.75. Paragraphs below threshold are flagged for burst correction.
Burst Pattern Generation
Generates a target sentence-length distribution using a gamma distribution model fit to authentic human writing corpora. Short sentences (5–12 words) are interspersed with longer ones (20–35 words) in natural clusters.
Structural Reshaping
Splits long uniform sentences into short+long pairs, or merges short adjacent sentences into flowing compound structures — preserving semantic content while changing length profile.
Rhythm Validation
Validates the reshaped text with SentenceValidator™ to ensure no fragments are created, then re-measures CV to confirm the rhythm signature matches human baseline.
Key Metrics
Use Cases
- Normalizing AI-text burstiness to pass GPTZero rhythm analysis
- Academic writing where AI sentence uniformity must be avoided
- Long-form content with authentic reading rhythm variation
- Adding natural complexity peaks to flat AI-generated explanations
Try BurstInjector™ Now
Powered by our proprietary technology stack. Available directly in the TextHumanize tools and via REST API.