Open Voice Classification
Collection
audio classifiers
β’
4 items
β’
Updated
Common-Voice-Gender-Detection is a fine-tuned version of
facebook/wav2vec2-base-960h
for binary audio classification, specifically trained to detect speaker gender as female or male. This model leverages theWav2Vec2ForSequenceClassification
architecture for efficient and accurate voice-based gender classification.
Wav2Vec2: Self-Supervised Learning for Speech Recognition : https://arxiv.org/pdf/2006.11477
Classification Report:
precision recall f1-score support
female 0.9705 0.9916 0.9809 2622
male 0.9943 0.9799 0.9870 3923
accuracy 0.9846 6545
macro avg 0.9824 0.9857 0.9840 6545
weighted avg 0.9848 0.9846 0.9846 6545
Class 0: female
Class 1: male
pip install gradio transformers torch librosa hf_xet
import gradio as gr
from transformers import Wav2Vec2ForSequenceClassification, Wav2Vec2FeatureExtractor
import torch
import librosa
# Load model and processor
model_name = "prithivMLmods/Common-Voice-Geneder-Detection"
model = Wav2Vec2ForSequenceClassification.from_pretrained(model_name)
processor = Wav2Vec2FeatureExtractor.from_pretrained(model_name)
# Label mapping
id2label = {
"0": "female",
"1": "male"
}
def classify_audio(audio_path):
# Load and resample audio to 16kHz
speech, sample_rate = librosa.load(audio_path, sr=16000)
# Process audio
inputs = processor(
speech,
sampling_rate=sample_rate,
return_tensors="pt",
padding=True
)
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
probs = torch.nn.functional.softmax(logits, dim=1).squeeze().tolist()
prediction = {
id2label[str(i)]: round(probs[i], 3) for i in range(len(probs))
}
return prediction
# Gradio Interface
iface = gr.Interface(
fn=classify_audio,
inputs=gr.Audio(type="filepath", label="Upload Audio (WAV, MP3, etc.)"),
outputs=gr.Label(num_top_classes=2, label="Gender Classification"),
title="Common Voice Gender Detection",
description="Upload an audio clip to classify the speaker's gender as female or male."
)
if __name__ == "__main__":
iface.launch()
male
female
Common-Voice-Gender-Detection
is designed for: