abdelhaqueidali/Amazigh-Lyrics-Collection

Dataset Card for Amazigh Lyrics Dataset

This dataset is a curated collection of Amazigh music lyrics transcribed in Tifinagh script using the standard orthography. It serves as an open resource to address the acute scarcity of structured text data types for modern Amazigh digital applications.

Dataset Details

Dataset Description

The Amazigh Lyrics Dataset is a work-in-progress (WIP) corpus designed to consolidate musical oral tradition into a standardized digital format. The audio metadata fields (title, artist, album) are provided directly in Amazigh.

To prioritize linguistic uniformity and digital utility, the texts lean heavily toward standard spelling rules rather than transcribing exact local phonetic variants. While the dataset targets a diverse set of dialects, the content primarily features music from Morocco, deeply concentrated around the Southwestern region (Tashelhit), from Sous and Asamer.

• Curated by: Abdelhaque Id Ali
• Language(s) (NLP): Amazigh (Standard Moroccan Amazigh, written in Tifinagh script)
• License: Open for research and educational purposes (Fair Use / Copyright belongs to original owners)

Uses

Direct Use

• Training and fine-tuning Language Models (LLMs) on standard Tifinagh text structures.
• Automatic Speech Recognition (ASR) alignment when combined with external audio inputs.
• Linguistic research into Amazigh syntax, poetic vocabulary, and cross-dialectal standardization.

Out-of-Scope Use

Commercial redistribution or commercialization of raw lyrics without explicit clearance from the copyright holders.

Dataset Structure

The dataset currently exports as a table containing the following fields:

• title: The song title written in Amazigh.
• artist: The recording artist/band name.
• album: The album title (where available). The labeled songs here with "AI" are songs made using song generation tools by their creators.
• lyrics: The cleaned, plain-text lyrics in Tifinagh script, stripped of temporal metadata.

Dataset Creation

Curation Rationale

The Amazigh language remains highly under-resourced in the digital space. Text assets—especially dynamic cultural items like music lyrics—are heavily scarce and fragmented across online spaces. This project aims to provide high-quality, normalized Tifinagh data to empower developers and researchers.

Source Data

Data Collection and Processing

Lyrics are compiled from various oral and written recordings, mapped against matching audio targets, and processed. Timestamps and system bracket tags (such as [...] or <...>) are stripped during extraction to yield structured, plain-text columns.

Future Roadmap

• Streaming Integration: Future iterations will incorporate direct Spotify and YouTube URLs to bridge the text entries back to their original metadata sources and streaming platforms.
• Time Synchronization: Inclusion of precise, line-by-line .lrc timestamp data for synchronization workflows.
• Linguistic Tagging: Addition of language and localized dialect tags, while preserving the centralized standardized orthographic text structure.

Bias, Risks, and Limitations

• Dialectal Balance: The text collection is heavily skewed toward Moroccan varieties (Sous and Asamer regions). It may not fully represent Northern Moroccan (Rifian) or broader pan-Amazigh varieties at this current stage.
• Standardization over Phonetics: Because the dataset favours standard spelling conventions over raw auditory phonetic variations, researchers focusing strictly on exact localized phonetic acoustics should use it with caution.

Copyright & Takedown Policy

No copyright infringement is intended by this work. The full rights to all underlying lyrical compositions belong strictly to their respective authors and copyright holders. This dataset is compiled solely for educational preservation, language resource development, and digital standardization.

If you are a copyright holder or a representative of one and wish to have your material omitted or modified, please reach out via the contact information provided below to submit a removal request, and your content will be promptly excluded.

Dataset Card Contact

• Contact: Abdelhaque Id Ali
• Email: abdelhaque.idali@gmail.com