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Mohamed Fadil edited this page Oct 6, 2026 · 2 revisions
Arachne

Contrastive speech analytics & temporal flaw grounding

Multimodal AI Hackathon 2026 · Track C

Arachne compares a performance of a speech with a reference reading of the exact same text, measures where and how the delivery differs, and explains each difference with the feature, comparison, time span and rubric rule behind it.

A flagged region is a measurement against one chosen reference, tied to an explicit rule. It is not proof of a "wrong" delivery, of intent, or of any cause.

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I want to... Go to
Run it Getting Started
Understand the design Architecture
Build the dashboard against the API API Reference · Result Schema
See what each rule measures Rubric
Understand the data Dataset
Check how well it works Evaluation and Results · Stress Testing
See what's done and what's next Project Status · Roadmap
Know the caveats Limitations
Work on it with the team Team and Workflow · Contributing
Submit to Devpost Submission Checklist
Quick answers FAQ

Snapshot (6 Oct 2026)

Area State
Backend pipeline (alignment, features, 4 rubric rules, scoring) Complete, 9/9 tests passing
REST API and result schema Complete
Synthetic dev dataset (63 items) + evaluation + stress harness Complete
Dashboard In progress
Real recordings and human-reviewed labels Not started
WhisperX forced alignment on real audio Implemented, untested
Technical document, demo video, Devpost Not started

Submission: internal deadline 14 Oct 2026; the event page lists 12:15 AM IST on 15 Oct 2026. Feature freeze 12 Oct.

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