Back to corpus
proposalexperiment writeup candidatescore 24

Phase 3 Implementation Plan – Motion, Voice & Phrase Intelligence (Beta)

**Timeline:** Weeks 13-18 (6 weeks) **Status:** ~85% Complete - Integration phase in progress **Goal:** Beta release with motion/voice control, phrase recommendations, and UI deck lanes

Full HTML reader

Read the full artifact

Open in new tab

Extracted abstract or opening context

## Overview Phase 3 focuses on integrating motion and voice control, implementing phrase intelligence with online recommendations, and building the user interface. This phase transforms Echelon from a core audio engine into a complete performance instrument with AI-powered phrase suggestions and gesture/voice control. **Timeline:** Weeks 13-18 (6 weeks) **Status:** ~85% Complete - Integration phase in progress **Goal:** Beta release with motion/voice control, phrase recommendations, and UI deck lanes - [x] **13.1 DELL Motion Stream Bridge** - [x] Create `motion-bridge` crate in `echelon/crates/` - [x] Implement `DellMotionReceiver` struct - [x] Connect to Episode 1 motion pipeline (ready, needs API endpoint) - [x] Add `MotionEvent` enum - [x] Map motion events to scheduler actions - **Dependencies:** Episode 1 motion pipeline running - **Deliverable:** ✅ Motion bridge receives Episode 1 data and converts to Echelon events - [x] **13.2 Motion-to-Action Translator** - [x] Create `MotionTranslator` struct - [x] Implement threshold-based triggers - [x] Map motion gestures to quantized actions - [x] Integrate with `ActionExecutor` - **Dependencies:** Motion bridge (13.1) - **Deliverable:** ✅ Motion gestures trigger deck operations - [x] **13.3 Motion Calibration** - [x] Implement `MotionCalibrator` for device-specific tuning - [x] Add calibration UI/config - [x] Store calibration data per device - **Deliverable:** ✅ Calibration system allows per-device tuning

Promotion decision

What has to happen next

Attach run IDs, datasets, metrics, and reproduction commands.

Why this is not always a full paper yet

Corpus pages are public-safe readers for discovered workspace artifacts. They are not automatically final papers. A corpus item becomes a polished paper only after the editable source, evidence checkpoints, references, figures, render path, and release status are attached through the paper schema.