MuhammadQASIM111/Animal_Sound_Classification

1---2dataset_info:3  name: Animal Sound Classification Dataset4  type: audio-classification5  license: mit6  annotations_creators:7    - expert-generated8  language:9    - no-linguistic-content10  task_categories:11    - audio-classification12  pretty_name: Animal Sound Classification13  size_categories: 1K<n<10K14  tags:15    - animal-sounds16    - audio17    - sound-classification18    - environmental-sounds19    - MFCC20    - open-dataset21    - sound-recognition22  features:23    - name: filename24      type: string25    - name: mfcc_126      type: float6427    - name: mfcc_228      type: float6429    - name: mfcc_330      type: float6431    - name: mfcc_432      type: float6433    - name: mfcc_534      type: float6435    - name: mfcc_636      type: float6437    - name: mfcc_738      type: float6439    - name: mfcc_840      type: float6441    - name: mfcc_942      type: float6443    - name: mfcc_1044      type: float6445    - name: mfcc_1146      type: float6447    - name: mfcc_1248      type: float6449    - name: mfcc_1350      type: float6451  splits:52    - name: train53      num_bytes: 11440054      num_examples: 104555  creators:56    - name: Muhammad Qasim57      url: https://github.com/MuhammadQasim11158license: mit59---60 61# 🐾 Animal Sound Classification Dataset62 63> **A meticulously handcrafted dataset of labeled animal sounds for Machine Learning & Audio Classification tasks.**64> **Built with love, precision, and open-source spirit.**65 66---67 68## 📖 Dataset Details69 70### 📝 Dataset Description71 72The **Animal Sound Classification Dataset** contains curated audio clips of **dogs, cats, cows**, and more, extracted from longer recordings and meticulously trimmed to create clean, high-quality sound samples. Over a period of **two months**, I manually processed, trimmed, and labeled each audio file. I also prepared the dataset for ML pipelines by extracting **MFCC (Mel-Frequency Cepstral Coefficients)** features to ensure seamless integration for developers and researchers.73 74- **Curated by:** Muhammad Qasim75- **Funded by:** Self-initiated Open-Source Project76- **License:** MIT License77- **Language(s):** Non-linguistic (animal sounds)78 79---80 81## 🔗 Dataset Sources82 83- **Repository:** [Hugging Face Link](https://huggingface.co/datasets/MuhammadQASIM111/Animal_Sound_Classification)84 85---86 87## 🚀 Uses88 89### ✅ Direct Use90 91- Audio classification model training.92- Sound recognition AI systems.93- Educational apps that teach animal sounds.94- Wildlife and livestock sound monitoring AI.95 96### ❌ Out-of-Scope Use97 98- Speech Recognition tasks.99- Use in sensitive environments without proper augmentation.100- Misuse for deceptive simulations.101 102---103 104## 🗂️ Dataset Structure105 106### Data Instances107 108| Field Name | Type | Description |109|------------|------|-------------|110| filename | string | Name of the audio file |111| mfcc_1 | float64 | First MFCC feature |112| mfcc_2 | float64 | Second MFCC feature |113| ... | ... | ... |114| mfcc_13 | float64 | Thirteenth MFCC feature |115 116### Data Fields117 118- `filename`: Name of the audio file.119- `mfcc_1` to `mfcc_13`: Mel-frequency cepstral coefficients (MFCCs) extracted from the audio files.120 121### Data Splits122 123| Split | Number of Examples | Total Size |124|-------|--------------------|------------|125| Train | 1045 | 114.4 KB |126 127---128 129## 📥 Dataset Creation130 131### Curation Rationale132 133The dataset was created to facilitate research and development in the field of audio classification, particularly focusing on animal sounds. The goal is to provide a high-quality, ready-to-use dataset for machine learning practitioners and researchers.134 135### Source Data136 137#### Initial Data Collection and Normalization138 139- **Data Collection:** Audio clips were collected from various sources and manually trimmed to isolate individual animal sounds.140- **Annotations:** Each audio clip was labeled with the corresponding animal class.141- **Who are the annotators?** The annotations were generated by an expert.142 143### Personal and Sensitive Information144 145The dataset does not contain any personal or sensitive information.146 147---148 149## 📜 Additional Information150 151### Dataset Curators152 153Muhammad Qasim154 155### Licensing Information156 157MIT License158 159### Citation Information160 161