---
title: "Audio Dataset: Various Music Genres"
description: "This music genres dataset contains 500,000 studio-grade music tracks in lossless FLAC format, designed for music genre classification and detection tasks. It provides rich music…"
url: "https://unidata.pro/datasets/audio-dataset-various-music-genres/"
date_modified: "2025-12-09T11:16:42+03:00"
language: "en-US"
---
This music genres dataset contains 500,000 studio-grade music tracks in lossless FLAC format, designed for music genre classification and detection tasks. It provides rich music metadata, including detailed genre labels, instruments, and artist information, making it ideal training data for machine learning and deep learning models in audio analysis.

## Dataset Structure

### The Numbers Section

**Numbered list:** - **Number:** 500,000 — **Text:** Audio

### Tooltips Section

**Tooltip items:**

- **Name:** Machine Learning
- **Name:** Audio Processing
- **Name:** ASR
- **Name:** Voice Recognition

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Music tracks covering multiple eras, genres, regions, and instrumental combinations. |
| Data types | Audio |
| Tasks | Speech recognition, Music Generation |
| Number of audio files | 500,000 |
| Labeling | Metadata (id, name, audio_format, genres, var_tags, instruments, vocal_instrumental, artist_name, album_id, gender, duration, release date, acoustic electric, album_name, speed, language) |
| Gender | Male, Female |

**Media Slider:** - **Video on Slayder:** [https://unidata.pro/wp-content/uploads/2025/08/audio-dataset\_-various-music-genres-0a-audio.mp4](https://unidata.pro/wp-content/uploads/2025/08/audio-dataset_-various-music-genres-0a-audio.mp4)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1J5Pjh5J2U-byrpxAih2KVlYDPS1VYgrh?usp=sharing)

### Statistics - Charts

**Charts with Titles:**

- **Diagram:** ![](https://unidata.pro/wp-content/uploads/2025/08/audio-dataset-various-music-genres0a-image2.webp) — **caption above the graph:** Distribution by gender
- **Diagram:** ![](https://unidata.pro/wp-content/uploads/2025/08/audio-dataset-various-music-genres0a-image1.webp) — **caption above the graph:** Distribution by speed

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Audio Format | FLAC |
| Bit Depth | 16-bit / 24-bit |
| Sampling Rate | 44.1 kHz or higher (48 kHz for ~20 % of tracks) |
| Number of Channels | Stereo |

**Source and data collection methodology:** Source and collection methodology: Data was collected via crowdsourcing platforms.

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Music Genre Classification for Streaming Platforms — **Title:** Training AI Models to Recognize Musical Genres — **Text:** The music genre dataset provides a large collection of audio samples across multiple music genres, enabling music genre classification models to accurately label tracks. By analyzing audio features and genre metadata, developers can train machine learning and deep learning models to enhance recommendation systems and improve user experience on streaming services.
- **Industry:** Audio Analysis and Feature Extraction Research — **Title:** Developing Models for Music Signal Understanding — **Text:** This audio dataset supports research into audio analysis and feature extraction for music tracks. With diverse music genres and well-labeled genre labels, the dataset allows researchers to build classification tasks, test transfer learning techniques, and evaluate genre recognition models in a controlled environment for both academic and commercial applications.
- **Industry:** Automated Playlist Generation — **Title:** Creating Smart Playlists Using Genre Recognition — **Text:** The music tracks dataset can be used to train classification models that automatically categorize music by genre, helping developers generate personalized playlists. By leveraging audio signals, metadata, and audio clips, systems can detect different genres accurately, improving music discovery and enabling automated playlist curation for music streaming platforms.
- **Industry:** Educational and Research Applications in Music Technology — **Title:** Studying Genre Patterns and Audio Features — **Text:** Researchers and educators can use this music genre dataset to analyze musical genres, study genre classification techniques, and train models on audio files. The dataset’s large collection of music tracks provides diverse training data, enabling students and professionals to explore audio analysis, genre recognition, and machine learning applications in music technology research.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** Can I get a sample of this audio dataset before buying? — **Answer:** Yes, free samples are available for trial and testing. Unidata provides smaller subsets of the dataset so you can evaluate the audio quality, annotation style, and data structure before committing to the full purchase of the larger dataset.
- **Question:** What is the source of the data for this music tracks dataset? — **Answer:** This dataset was collected via crowdsourcing platforms from legally permissible sources.
- **Question:** How was this music data collected? — **Answer:** The data was collected via a structured methodology using crowdsourcing platforms.
- **Question:** How are Unidata datasets licensed? — **Answer:** Unidata datasets follow a dual-licensing model. Free samples are provided for trial and testing, while the full datasets, including this comprehensive music genre collection, are available exclusively through purchase.
- **Question:** Are Unidata datasets compliant with data privacy regulations like GDPR? — **Answer:** Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is collected from legally permissible sources to ensure ethical and lawful usage in your audio analysis and machine learning projects.
- **Question:** How are the audio files stored and managed? — **Answer:** Unidata stores all datasets securely on AWS cloud infrastructure, ensuring high availability and scalability. Our storage practices are aligned with ISO 27001 and ISO 27701 standards, guaranteeing a secure, reliable, and privacy-focused environment for all audio files and music metadata.
- **Question:** How long does delivery take after purchasing the dataset? — **Answer:** After you submit a request and complete the necessary documents and payment, the dataset will be delivered within 3 to 10 days.
- **Question:** Why is detailed music metadata valuable for machine learning? — **Answer:** Rich metadata allows developers to filter tracks by genre, instruments, vocal style, language, tempo, and other musical characteristics. This enables more precise dataset preparation, supervised learning, and evaluation of music information retrieval models.
- **Question:** What makes this music genres dataset suitable for AI research? — **Answer:** The dataset combines a large-scale collection of studio-quality music recordings with comprehensive metadata covering genres, instruments, artists, and musical characteristics. This makes it valuable for benchmarking machine learning models, developing foundation models for music understanding, and advancing music AI research.

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