Real-Time Ethiopian Sign Language Translation. Zero Video Latency.
Ergaa replaces high-bandwidth video streams with edge-extracted coordinate metadata—enabling autonomous, private VoIP communication between Ethiopian Sign Language (EthSL) and spoken Amharic over 4G LTE.
95% bandwidth reduction over standard H.264 video.
End-to-end translation latency (well under the 200 ms ITU limit).
Local NLP grammatical reordering (Amharic ↔ EthSL spatial syntax).
{
"frame_seq": 88412,
"timestamp_us": 1756582491024,
"landmarks": {
"dominant_hand": [[0.512, 0.634, -0.042], [0.521, 0.648, -0.038], ... (21 pts)],
"non_dominant_hand": [[0.312, 0.420, 0.012], [0.318, 0.435, 0.010], ... (21 pts)],
"facial_expression": [[0.498, 0.231, 0.005], ... (18 key points)],
"spatial_trajectory": { "motion_vector": [-0.014, 0.082, 0.001], "velocity_mag": 0.42 }
},
"bandwidth_reduction": "95.9% vs raw H.264 720p stream"
}Why Video Calls Fail for Sign Language VoIP
Sign language requires continuous 24+ FPS motion clarity and sub-200ms latency. On standard cellular infrastructure, traditional video streaming breaks down completely.
Cellular Bandwidth Bottlenecks on 4G LTE
Standard 1080p/720p video streaming requires 1.2–3.2 Mbps. On throttled or congested mobile links (e.g. Ethio Telecom), calls suffer chronic frame drops and unreadable sign articulation.
Extracts 3D skeletal landmarks locally, requiring just 94 Kbps (95% bandwidth drop)—running fluidly even on degraded 2G/3G/4G cellular connections.
Buffer Delay & Head-of-Line Packet Blocking
Traditional video jitter buffers and TCP/RTP retransmissions introduce 100–300ms of lag, breaking the tight 200ms ITU limit needed for dynamic two-way medical dialogue.
Transmits coordinate arrays over unordered SCTP DataChannels over UDP. Dropped frames are immediately superseded by the latest 24 FPS pose with < 10ms buffer delay.
Patient Privacy & Visual PHI Exposure
Transmitting raw video streams sends the patient's face, home environment, and medical surroundings to remote servers, creating regulatory and confidentiality liabilities.
No pixels or video frames ever leave the patient's device. MediaPipe extracts mathematical coordinates on Phone A, ensuring 100% cryptographic visual anonymity.
Complex Spatial Syntax Mismatch
Direct word-for-word sign translation fails because Ethiopian Sign Language uses complex spatial loci, non-manual facial grammar, and SOV structures distinct from spoken Amharic.
On-device linguistic engine maps 3D spatial loci and facial morphemes into grammatically accurate spoken Amharic and converts medical speech back to 3D EthSL avatars.
Decoupling Computer Vision from Video Streaming
Traditional video VoIP streams (1080p @ 3.2 MB/s) collapse on volatile 4G mobile networks. Ergaa executes computer vision extraction locally on Phone A, transmitting only high-fidelity 3D skeletal coordinates to drive real-time sign language avatars and spoken Amharic speech.
Phone A (Deaf User)
MediaPipe Holistic local inference (21 hand landmarks, 468 face mesh coordinates) capturing at 24 FPS directly on-device without uploading video.
Coordinate Packaging
Serialization into a lightweight 4.89 KB JSON payload using fixed-point coordinate delta compression, slashing raw video bandwidth by 95%.
Network Layer
WebRTC DataChannel (unreliable/unordered SCTP over UDP) bypassing Ethio Telecom 4G packet-loss and Head-of-Line blocking.
Phone B / Cloud Node
Localized Hybrid NLP mapping medical syntax into EthSL gestures + WebGL 3D Avatar rendering, reordering spatial syntax into spoken Amharic in 0.18ms.
{
"session_id": "ethsl_live_0x9941a",
"timestamp": 1725042000,
"frame_index": 4821,
"fps_actual": 24.0,
"hand_landmarks": {
"dominant_hand": [
{ "id": 0, "name": "WRIST", "x": 0.5124, "y": 0.6341, "z": -0.0421, "v": 0.99 },
{ "id": 4, "name": "THUMB_TIP", "x": 0.5218, "y": 0.6482, "z": -0.0384, "v": 0.98 },
{ "id": 8, "name": "INDEX_FINGER_TIP", "x": 0.5342, "y": 0.6619, "z": -0.0412, "v": 0.99 },
"... [18 additional 3D coordinates truncated]"
],
"non_dominant_hand": [
{ "id": 0, "name": "WRIST", "x": 0.3129, "y": 0.4201, "z": 0.0124, "v": 0.99 },
"... [20 additional 3D coordinates truncated]"
]
},
"face_mesh": [
{ "idx": 1, "region": "NOSE_TIP", "x": 0.4982, "y": 0.2314, "z": 0.0051 },
{ "idx": 33, "region": "LEFT_EYE_INNER", "x": 0.5012, "y": 0.2389, "z": 0.0048 },
"... [466 facial contour points truncated]"
],
"spatial_syntax_cue": {
"dominant_locus": "UPPER_CHEST_RIGHT",
"motion_vector": [-0.0142, 0.0821, 0.0019],
"glottal_morph": "AMHARIC_ASPIRATED_P",
"confidence": 0.9984
}
}Standard Video VoIP vs. Ergaa Coordinate Protocol
By eliminating heavy raster video encoding in favor of quantized 3D skeletal landmark arrays, Ergaa achieves orders-of-magnitude reductions in bandwidth, latency, and cellular jitter.
HEAD-TO-HEAD SPECIFICATION BREAKDOWN
EthSL-Optimized Protocol v1.4| METRIC | STANDARD VIDEO VOIP (H.264/WebRTC Video) | ERGAA COORDINATE PROTOCOL | ARCHITECTURAL ADVANTAGE |
|---|---|---|---|
Payload Size Per-frame transmitted data over cellular interface | 50–150 KB | 4.89 KB | 95.2% Payload Reduction |
Required Bandwidth Minimum sustainable network throughput per stream | 1.2 Mbps | 94 Kbps | Operates on 2G/3G/4G throttled links |
Buffer Delay Jitter buffer and decoding queue latency | 100–300 ms | < 10 ms | Instantaneous mesh rendering |
Network Resilience Behavior during severe packet loss & carrier congestion | High frame drop & frozen video | Smooth WebGL rendering (No HOL blocking) | Unordered SCTP DataChannel resilience |
Deploy Ergaa in Healthcare & Accessibility Pilots
We collaborate with hospitals, clinics, assistive non-profits, and telecom operators to deploy real-time, low-bandwidth Ethiopian Sign Language (EthSL) translation for urgent healthcare triage and deaf community VoIP access.
Emergency Medical Triage Support
Two-way speech-to-avatar and sign-to-speech for clinicians and deaf patients during critical intake.
Low-Bandwidth 4G / 3G Resilience
Engineered to function smoothly on cellular data connections with 95% bandwidth reduction.
Direct Engineering & ML Collaboration
Hands-on support from our core AI compiler and linguistics team for on-site integration.