> ## Documentation Index
> Fetch the complete documentation index at: https://developer.sanas.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agentic SE Overview

> Clean, isolate, and enhance audio before it reaches your ASR/STT engine — purpose-built for voice agents, IVR, and machine listeners.

# Agentic Speech Enhancement

> Cleaner audio in, more accurate transcripts out.

Sanas **Agentic Speech Enhancement (Agentic SE)** models prepare audio for machines rather than human listeners. They isolate the primary speaker, strip background noise and distant voices, and hand a clean signal to your speech-to-text (ASR/STT) engine — reducing recognition errors and making downstream voice-agent behavior more reliable.

All Agentic SE models are optimized for <span class="tag-h2m">Human ↔ Machine</span> experiences, where the "listener" is a transcription engine, IVR, or voice bot.

## Why Agentic SE

* **Lower word error rates** — cleaner input audio reduces Relative Word Error Rate (RWERR) for your ASR/STT.
* **Primary-speaker isolation** — removes distant voices and background noise so the agent hears one speaker.
* **Multi-speaker awareness** — a Standard variant preserves all human speech when background conversation carries context.
* **Telephony-ready** — a variant tuned for 8kHz narrowband phone audio.

## Core models

<CardGroup cols={3}>
  <Card title="Agentic SE · Voice Isolation (General)" icon="robot" href="/Docs/Models/Human-Machine/Agentic-SE-Voice-Isolation">
    **`AGENTIC_VI_G_SE`** Removes background noise and distant voices for complete voice isolation of the primary speaker's audio stream.
  </Card>

  <Card title="Agentic SE · Voice Isolation (Telephony)" icon="robot" href="/Docs/Agentic-SE-Voice-Isolation-Telephony">
    **`AGENTIC_VI_GT_SE`** Telephony-optimized variant of Voice Isolation for 8kHz narrowband audio.
  </Card>

  <Card title="Agentic SE · Standard" icon="robot" href="/Docs/Agentic-SE-Standard">
    **`AGENTIC_ST_SE`** Removes background noise while preserving all human speech for multi-speaker environments.
  </Card>
</CardGroup>

## Model comparison

| Model                                                            | Description                                                                        | Best For                                                                | Latency | Sample rate | RWERR (avg) |
| ---------------------------------------------------------------- | ---------------------------------------------------------------------------------- | ----------------------------------------------------------------------- | ------- | ----------- | ----------- |
| `AGENTIC_VI_G_SE`<br />Agentic SE — Voice Isolation (General)    | Removes all background noise and non-primary voices for complete speaker isolation | Single-speaker isolation for voice agents, IVR, phone bots              | \~100ms | 16kHz       | 5–30%       |
| `AGENTIC_VI_GT_SE`<br />Agentic SE — Voice Isolation (Telephony) | Telephony-optimized variant for 8kHz narrowband audio                              | Telephony voice agents, IVR, contact centers                            | \~100ms | 8kHz        | 5–30%       |
| `AGENTIC_ST_SE`<br />Agentic SE — Standard                       | Removes background noise while keeping all human speech audible                    | Multi-speaker environments where background conversations carry context | \~100ms | 16kHz       | 5–30%       |

## How to choose

* Pick **Voice Isolation — General (`AGENTIC_VI_G_SE`)** when you want a single, isolated speaker stream for a voice agent, IVR, or phone bot at 16kHz.
* Pick **Voice Isolation — Telephony (`AGENTIC_VI_GT_SE`)** for the same isolation on 8kHz narrowband telephony audio.
* Pick **Standard (`AGENTIC_ST_SE`)** for multi-speaker environments where you need background noise removed but *all* human speech preserved.

<Note>
  Agentic SE models are designed to run **before** your ASR/STT engine to improve transcription accuracy. For audio intended for human listeners, use the [Speech Enhancement](/Docs/Models/Overview) (Human ↔ Human) models instead.
</Note>