Voice gender classifier for European voice AI (1MB, ONNX, 4ms)
Hi, I'm Kamil and I'm a founder of Applied AI agency in Warsaw, Poland. We've trained a small <1MB voice classifier model that runs on CPU in 4ms. Can be run next to silero VAD in voice AI deployments. What we noticed in production deployments of voice assistants in Contact Centers in EU is that human consultants pick up immediately how to inflect verbs and ajdectives after one utterance from the caller. But voice AI agents don't know it until 1-2 minutes into the call when they are either corrected or the caller uses explicitly words with male/female form a couple of times. Our model…
Voice gender classifier for European voice AI (1MB, ONNX, 4ms) launched on May 12, 2026 with 5 votes, #2,008 of 20,538 launches that month and more than 75% of that year's launches.
What it does
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A lightweight voice gender classifier designed as a preprocessing component for real-time voice AI pipelines. Runs on CPU in under 5 ms, exported to ONNX, no PyTorch required at inference time. Model size: 0.64 MB | Parameters: 166K | Inference: ~4 ms (CPU, single-threaded) We build voice AI assistants for clients across European markets. In languages with grammatical gender (Polish, German, French, Spanish, Italian), addressing someone requires correct inflection of adjectives, verb forms, and honorifics. Human agents recognise the caller's gender from their voice in the first seconds of a call and adjust naturally. This model gives voice pipelines the same capability. import numpy as np…from huggingface.co
In the maker’s words, at launch
Hi, I'm Kamil and I'm a founder of Applied AI agency in Warsaw, Poland. We've trained a small <1MB voice classifier model that runs on CPU in 4ms. Can be run next to silero VAD in voice AI deployments. What we noticed in production deployments of voice assistants in Contact Centers in EU is that human consultants…
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