Find Genre

Find Genre is a specialized tool for automatic music genre identification using advanced artificial intelligence algorithms. Its primary function is to analyze audio tracks to determine their predominant style, making file classification easier for both industry professionals and hobbyists. The system allows users to process files uploaded directly from their computer in common formats like MP3, WAV, FLAC, M4A, and OGG, while also offering compatibility with external links from platforms such as YouTube and SoundCloud.

The underlying technology of Find Genre employs a trained neural network that examines short segments of a music track to evaluate its structure and rhythm. As a result of the analysis, the user receives a ranked list of potential genres, each accompanied by a confidence percentage. This probabilistic approach allows users to understand not only the primary genre but also the secondary influences within the composition, providing a precise answer to the question of what genre a song belongs to.

In addition to style detection, the application features optional functions to extract technical audio attributes, making it a valuable resource for AI track analysis. The additional data it can provide includes:

• Detection of BPM (beats per minute) and musical key.
• Measurement of loudness levels (RMS and LUFS).
• Analysis of spectral shape and dynamic range.
• A track history of processed files to facilitate easy access to previous searches.

The workflow is straightforward and functional: after logging in, users can begin detection instantly. This tool is especially useful for those who need to tag music accurately and quickly without relying on subjective manual processes. Although the analysis requires an internet connection and does not currently support batch processing, its ability to interpret both streaming links and local files makes it a versatile solution for music catalog organization and audio content curation. The system ensures that every result is the product of a technical, data-driven analysis, providing a solid foundation for classifying any audio library.