AUTOMATION

Inject Voice Gender Classification into Voice AI Agent Context

Use a lightweight 1MB ONNX model to detect caller gender from first utterance and improve linguistic accuracy in voice agents

Updated: 5/14/2026
Difficulty
easy
Time
15m
Use Case
Improve voice AI agent linguistic accuracy in contact centers by detecting caller gender early and injecting it into the system prompt
Popularity
0 views

About this automation

Deploy a <1MB ONNX voice gender classifier (4ms latency on CPU) alongside Silero VAD in voice AI pipelines. The classifier runs on the first utterance and outputs gender classification, which is injected as context into the agent's system prompt. This allows voice agents to inflect verbs and adjectives correctly from the start, matching human consultant behavior and improving adoption in EU contact center deployments.

How to implement

1

Load the ONNX gender classifier model from Hugging Face (syntropicsignal-ai/gender-voice-classifier)

2

Integrate the classifier into your voice pipeline after VAD detection

3

Run inference on the first caller utterance (4ms latency on CPU)

4

Extract gender classification output

5

Inject classification into the voice agent's system prompt as context (e.g., 'Caller gender: female, use feminine forms')

6

Continue conversation with linguistically accurate responses