fr3on/egyptian-songs

Egyptian Arabic Songs Dataset 🎵

Dataset Description

This dataset contains 3,063 lines of Egyptian Arabic song lyrics with English translations, spanning 280 songs from 1983-2021. The dataset features natural Egyptian Arabic dialect (العامية المصرية) as used in popular music, with automatic genre classification and line-type detection.

Languages

• —Source: Egyptian Arabic (ar_EG) - Colloquial dialect in music
• —Target: English (en)

Dataset Summary

Egyptian Arabic music represents a rich cultural tradition and is one of the most influential Arabic music styles globally. This dataset provides:

• —Authentic Egyptian Arabic lyrics from popular songs
• —Poetic and colloquial expressions
• —Genre-classified content for theme-aware training
• —Temporal context (release years)
• —Song and album metadata for context

Dataset Structure

Data Format

Each entry contains:

{
  "id": "song0001_line0042",
  "arabic": "المدينة قلبها زحمة بالهموم",
  "english": "The heart of the city teems with sorrow.",
  "song_name": "المدينة",
  "album_name": "يا طريق",
  "year": 1983,
  "song_id": 1,
  "dialect": "egyptian",
  "language": "ar",
  "language_variant": "ar_EG",
  "content_type": "song_lyrics",
  "line_type": "verse",
  "genre": "sadness"
}

Data Fields

Dataset Statistics

Overview

• —Total Lines: 3,063
• —Unique Songs: 280
• —Unique Albums: 35
• —Year Range: 1983-2021
• —Unique Genres: 9
• —Average Arabic Length: 28.6 characters
• —Average English Length: 49.2 characters

Genre Distribution

Line Type Distribution

• —verse: 2,458 (80.2%)
• —chorus: 605 (19.8%)

Temporal Distribution

Top Songs by Line Count

Genres Explained

This dataset includes automatic genre/theme classification using keyword-based detection:

• —romance - Love songs, relationships, affection
• —sadness - Melancholic themes, heartbreak, sorrow
• —nostalgia - Memories, past times, longing
• —hope - Optimistic themes, dreams, aspirations
• —social - Social commentary, life observations
• —patriotic - National pride, homeland themes
• —spiritual - Religious or spiritual content
• —celebration - Joyful occasions, festivities
• —general - General themes without specific classification

Use Cases

✅ Recommended Use Cases

• —Egyptian Arabic Translation: Train translation models for colloquial Egyptian
• —Lyric Generation: Generate Egyptian Arabic song lyrics
• —Genre-Aware Models: Train models that understand musical themes
• —Cultural NLP: Study Egyptian culture through music
• —Dialect Research: Research Egyptian Arabic characteristics in artistic contexts
• —Music Information Retrieval: Lyrics-based music analysis
• —Cross-lingual Understanding: Arabic-English semantic alignment

⚠️ Limitations

• —Domain Scope: Limited to song lyrics (poetic/artistic language)
• —Size: 3,063 lines (moderate size for specialized tasks)
• —Time Period: 1983-2021 (may not reflect modern slang)
• —Artist Coverage: Limited to specific artists/albums
• —Line Context: Individual lines may lack full song context
• —Genre Accuracy: Automatic genre detection may have errors

Loading the Dataset

Using Hugging Face Datasets

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("fr3on/egyptian-songs")

# Access the data
print(dataset['train'][0])

# Filter by genre
romance_songs = dataset['train'].filter(lambda x: x['genre'] == 'romance')

# Filter by year
songs_80s = dataset['train'].filter(lambda x: 1980 <= x['year'] < 1990)

# Filter by song
specific_song = dataset['train'].filter(lambda x: x['song_id'] == 1)

Using Pandas

import pandas as pd

# Load Parquet file directly
df = pd.read_parquet("data/train-00000-of-00001.parquet")

# Analyze genres
print(df['genre'].value_counts())

# Get all lines from a specific song
song_lines = df[df['song_name'] == 'المدينة'].sort_values('id')

# Filter by year range
df_90s = df[(df['year'] >= 1990) & (df['year'] < 2000)]

Training Examples

Translation Model (Lyric-Aware)

from datasets import load_dataset
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, Seq2SeqTrainer

# Load dataset
dataset = load_dataset("fr3on/egyptian-songs")

# Load model for Arabic-English translation
model_name = "Helsinki-NLP/opus-mt-ar-en"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Tokenize
def preprocess(examples):
    inputs = tokenizer(examples['arabic'], truncation=True, max_length=128)
    targets = tokenizer(examples['english'], truncation=True, max_length=128)
    inputs['labels'] = targets['input_ids']
    return inputs

tokenized = dataset.map(preprocess, batched=True)

# Train
trainer = Seq2SeqTrainer(
    model=model,
    train_dataset=tokenized['train'],
    eval_dataset=tokenized['test']
)
trainer.train()

Genre-Aware Text Generation

from datasets import load_dataset
from transformers import GPT2LMHeadModel, GPT2Tokenizer

dataset = load_dataset("fr3on/egyptian-songs")

# Train separate models per genre
for genre in ['romance', 'sadness', 'hope']:
    genre_data = dataset['train'].filter(lambda x: x['genre'] == genre)
    print(f"Training {genre} model with {len(genre_data)} examples")
    # Train genre-specific model

Lyric Generation

from datasets import load_dataset

dataset = load_dataset("fr3on/egyptian-songs")

# Prepare for language modeling
def prepare_for_lm(example):
    return {'text': f"<|song|>{example['song_name']}<|genre|>{example['genre']}<|lyrics|>{example['arabic']}<|endoftext|>"}

lm_dataset = dataset.map(prepare_for_lm)
# Train GPT-style model for lyric generation

Data Collection & Processing

Source

• —Origin: Egyptian song lyrics with professional translations
• —Quality: Human-curated translations
• —Cultural Context: Authentic Egyptian musical heritage

Processing Pipeline

1. 1.Extraction: Load from Excel with metadata
2. 2.Cleaning: Remove empty/short lines, whitespace normalization
3. 3.Deduplication: Hash-based duplicate removal
4. 4.Genre Detection: Automatic classification using keyword matching
5. 5.Line Type Detection: Classify verses, chorus, instrumental sections
6. 6.Validation: Quality checks and statistics generation
7. 7.Format Conversion: Export to JSONL and Parquet

Data Quality

• —✅ Deduplicated using MD5 hash matching
• —✅ Filtered lines < 3 characters
• —✅ Removed rows with missing translations
• —✅ Normalized whitespace
• —✅ Validated Arabic-English text pairs
• —✅ Preserved song/album context

Considerations for Using the Data

Egyptian Arabic in Music

Egyptian Arabic in songs has unique characteristics:

• —Poetic Language: More metaphorical and artistic than everyday speech
• —Rhyme Schemes: Traditional Arabic poetry patterns (قافية)
• —Colloquialisms: Mix of formal and informal expressions
• —Cultural References: Egyptian-specific idioms and references
• —Emotional Intensity: Heightened expressive language

Recommended Training Approaches

1. 1.Fine-tune on this dataset after pre-training on general Egyptian Arabic
2. 2.Combine with speech data for richer dialect representation
3. 3.Use genre filtering for domain-specific applications
4. 4.Preserve song context when possible for narrative understanding
5. 5.Consider temporal aspects - language evolves over decades
6. 6.Balance genres if training general-purpose models

Ethical Considerations

• —Copyright: Original songs are copyrighted; dataset for research purposes
• —Cultural Sensitivity: Respect Egyptian cultural and musical heritage
• —Attribution: Credit original artists and composers
• —Representation: One slice of Egyptian musical culture
• —Usage: For educational, research, and non-commercial purposes

License

This dataset is released under the CC-BY-4.0 License.

⚠️ Note: Original songs are copyrighted. This dataset is intended for research, education, and non-commercial use only.

Citation

If you use this dataset in your research, please cite:

@dataset{egyptian_songs_2025,
  title={Egyptian Arabic Songs Dataset},
  author={fr3on},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/fr3on/egyptian-songs}
}

Acknowledgments

• —Source: Egyptian song lyrics with translations
• —Processing: Automatic genre and line-type detection
• —Cultural Heritage: Egyptian musical tradition

Version History

• —v1.0.0 (2025-12-18): Initial release
• —3,063 lyric lines
• —280 songs from 35 albums
• —1983-2021 temporal coverage
• —9 genre categories
• —Automatic genre and line-type detection

Keywords: Egyptian Arabic, ar_EG, dialect, colloquial, music, lyrics, songs, translation, NLP, Egyptian culture, Arabic poetry, song generation

Dataset Size: 3,063 lines | Format: Parquet | License: CC-BY-4.0