Eleniia AI Whitepaper

Core Technologies

Multi-Modal Speech Recognition

Eleniia employs a hybrid model combining CNNs and LSTMs for real-time voice-to-text transcription with 99.3% accuracy on standard datasets.

Our speech recognition engine integrates multiple neural architectures to handle both structured conversations and free-form speech, with adaptive noise filters and speaker diarization for multi-person interactions.

Accuracy
99.3% on Mozilla Common Voice

Latency
180ms (90th percentile)

Languages
137+ native languages supported

Wake Words
Customizable with 160+ pre-trained models

The language model backbone is a lightweight MoE (Mixture of Experts) architecture optimized for voice interactions, with memory-efficient context windows for continuous conversations.

Distributed training across 128 TPU v4 chips
On-device inference with 1.5GB footprint
Real-time sentiment analysis with 97.8% precision

Note: All models trained on de-identified dataset of 45 million voice samples with consent.

Voice Cloning Module

Our zero-shot voice cloning allows users to create 200 distinct voice profiles from just 30 seconds of original audio sample.

Eleniia AI Whitepaper