CuriousMonkey7/HumAware-VAD

HumAware-VAD: Humming-Aware Voice Activity Detection

📌 Overview

HumAware-VAD is a fine-tuned version of the [Silero-VAD](https://github.com/snakers4/silero-vad/tree/master) model, trained to distinguish humming from actual speech. Standard Voice Activity Detection (VAD) models, including Silero-VAD, often misclassify humming as speech, leading to inaccurate speech segmentation. HumAware-VAD improves upon this by leveraging a custom dataset ([HumSpeechBlend](https://huggingface.co/datasets/CuriousMonkey7/HumSpeechBlend)) to enhance speech detection accuracy in the presence of humming.

🎯 Purpose

The primary goal of HumAware-VAD is to:

• —Reduce false positives where humming is mistakenly detected as speech.
• —Enhance speech segmentation accuracy in real-world applications.
• —Improve VAD performance for tasks involving music, background noise, and vocal sounds.

🗂️ Model Details

• —Base Model: Silero-VAD
• —Fine-tuning Dataset: HumSpeechBlend
• —Format: JIT (TorchScript)
• —Framework: PyTorch
• —Inference Speed: Real-time

📥 Download & Usage

🔹 Install Dependencies

pip install torch torchaudio

🔹 Load the Model

import torch

def load_humaware_vad(model_path="humaware_vad.jit"):
    model = torch.jit.load(model_path)
    model.eval()
    return model

vad_model = load_humaware_vad()

🔹 Run Inference

import torchaudio

waveform, sample_rate = torchaudio.load("data/0000.wav")
out = vad_model(waveform)
print("VAD Output:", out)

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🏆 Performance

Compared to the base Silero-VAD model, HumAware-VAD demonstrates: ✅ Lower false positives for humming ✅ Better segmentation of speech in mixed audio ✅ Maintained real-time inference capabilities

📊 Applications

• —Automatic Speech Recognition (ASR) Preprocessing
• —Noise-Robust VAD Systems
• —Speech Enhancement & Separation
• —Call Center & Voice Communication Filtering -->

📄 Citation

If you use this model, please cite it accordingly.

@model{HumAwareVAD2025,
  author = {Sourabh Saini},
  title = {HumAware-VAD: Humming-Aware Voice Activity Detection},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/CuriousMonkey7/HumAware-VAD}
}