updated readme

README.md

@@ -5,8 +5,76 @@ tags:
 - vad
 - humming
 ---
+# HumVAD Dataset: Humming vs Speech Detection
 
-# HumVAD Dataset 🗣️🎶
+## 📌 Overview
+**HumVAD** is a dataset designed to fine-tune **Voice Activity Detection (VAD) models** to distinguish between **humming** and actual speech. Current VAD models often misclassify humming as speech, leading to incorrect segmentation in speech processing tasks. This dataset provides a structured collection of humming audio interspersed with speech to help improve model accuracy.
 
-**HumVAD** is a dataset designed to fine-tune Voice Activity Detection (VAD) models to differentiate **humming** from speech.  
-This dataset contains humming sounds mixed with short speech segments to address the issue where VAD models mistakenly detect humming as speech.
+## 🎯 Purpose
+The dataset was created to address the challenge where **humming is mistakenly detected as speech** by existing VAD models. By fine-tuning a VAD model with this dataset, we aim to:
+- Improve **humming detection** accuracy.
+- Ensure **clear differentiation between humming and speech**.
+- Enhance **real-world speech activity detection**.
+
+## 📜 Dataset Creation Strategy
+To build this dataset, the following methodology was used:
+1. **Humming Audio Collection**: Various humming recordings were sourced from the "MLEnd-Hums-and-Whistles" dataset.
+2. **Speech Insertion**: Short speech segments were extracted from "Global Recordings Network" datasets.
+3. **Mixing Strategy**:
+   - Humming is the dominant sound in each sample.
+   - Speech is **randomly inserted** at different timestamps in the humming audio.
+   - Speech timestamps were carefully annotated to facilitate supervised learning.
+
+### 🔹 Metadata Explanation
+The dataset includes the following metadata columns:
+
+| Column Name                      | Description |
+|----------------------------------|-------------|
+| `humming_song`                  | The song or source from which the humming was derived. |
+| `humming_Interpreter`           | The individual or source providing the humming. |
+| `humming_audio_used`            | Index of the humming audio in the original dataset. |
+| `humming_transcript`            | Transcription of the humming (if available). |
+| `globalrecordings_audio_used`   | Speech segment sourced from Global Recordings Network. |
+| `globalrecordings_audio_ts_used` | The start and end timestamps of the speech segment in the original recording. |
+| `mixed_audio_path`              | The path to the final mixed audio file (humming + speech). |
+| `mixed_audio_speech_ts`         | The timestamps where speech appears within the mixed audio file. |
+
+
+## 📥 Download and Usage
+
+### 🛠️ Loading the Dataset
+Since the dataset does not have predefined splits, you can load it using the following code:
+
+```python
+import pandas as pd
+from datasets import load_dataset
+
+# Load dataset from Hugging Face
+dataset = load_dataset("YOUR_USERNAME/HumVAD", split=None)  # No predefined splits
+
+# Load metadata
+metadata = pd.read_feather("metadata.feather")  # Load the Feather metadata
+print(metadata.head())
+```
+
+### 🔊 Loading Audio Files
+To work with the audio files:
+```python
+import torchaudio
+
+waveform, sample_rate = torchaudio.load("data/audio1.wav")
+print(f"Sample Rate: {sample_rate}, Waveform Shape: {waveform.shape}")
+```
+
+## 📄 Citation
+If you use this dataset, please cite it accordingly.
+
+```
+@dataset{HumVAD2025,
+  author = {Sourabh Saini},
+  title = {HumVAD: Humming vs Speech Dataset},
+  year = {2025},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/CuriousMonkey7/HumAwareVAD}
+}
+```