AGENTIC_ST_SE) model is designed to improve Automatic Speech Recognition (ASR) accuracy in noisy multi-speaker environments. Unlike traditional speech enhancement optimized for human perception, this model preserves the acoustic and phonetic information that ASR systems depend on, including distant human speech, while removing environmental noise.
Hear the Difference
Removes environmental background noise while preserving distant human speech, ensuring ASR captures every speaker in multi-speaker environments where background conversations carry context.Before · Multiple speakers + background noise
After · All speakers preserved, noise removed
Performance Benchmarks
The following transcripts are generated from the audio samples above. The Oracle Transcript is the ground truth — the actual words spoken. The Source Transcript is the raw audio passed directly through the ASR system. The Sanas Transcript is the audio processed through the Sanas model first, then passed through the same ASR system. The Word Error Rate (WER) is calculated relative to the Oracle Transcript (0% WER), based on insertion, deletion, and substitution errors — bolded words below indicate these errors. WER percentage for each is shown at the bottom of the table.Test Environment
- Background: Indoor environment with TV audio playing at moderate volume
- ASR System: Deepgram Nova3 Streaming