text
stringlengths 64
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|---|---|
Melancholic Chinese ballad with soft acoustic guitar and emotional male vocals about resembling someone from the past
|
c-pop
|
Smooth Chinese R&B duet featuring gentle harmonies and minimalist production about unconditional feelings
|
c-pop
|
Dark Chinese trap-influenced track with heavy bass and auto-tuned vocals exploring emotional addiction
|
c-pop
|
Catchy pop track with playful lyrics about dating drama featuring upbeat production and confident female vocals
|
pop
|
Sultry electronic pop with breathy vocals and dark synths about intense desire and dangerous attraction
|
pop
|
Smooth R&B with layered harmonies and trap-influenced beats about relationship complications
|
r&b
|
Powerful anthem with fierce vocals celebrating female empowerment over hip-hop influenced production
|
r&b
|
Experimental bilingual track mixing Chinese and English with edgy electronic production and attitude
|
c-pop
|
Energetic cover with powerful vocals and rock-influenced arrangement building to explosive chorus
|
pop
|
Synth-pop perfection with dreamy production and lyrics about a complicated summer romance
|
pop
|
Ethereal pop with nostalgic production and wistful vocals about memories of past love
|
pop
|
Emotional ballad with soaring vocals and orchestral production about desperate love
|
pop
|
Vulnerable pop ballad with piano and strings about giving love one final chance
|
pop
|
Hyperpop anthem with glitchy production and autotuned vocals celebrating hedonistic partying
|
pop
|
Playful pop with witty wordplay and bouncy production about crushing on someone
|
pop
|
Electronic pop with dramatic production about awakening from emotional manipulation
|
pop
|
High-energy K-pop with video game inspired sounds and confident group vocals
|
k-pop
|
Solo K-pop debut with trap beats and fierce attitude showcasing individual star power
|
k-pop
|
Smooth R&B-pop with sultry vocals about possessive romance over minimalist beats
|
pop
|
Dreamy pop with West Coast vibes and catchy hooks about young love in California
|
pop
|
Fierce collaboration with heavy bass and confident dual vocals about irresistible chemistry
|
k-pop
|
Emotional pop with raw vocals processing heartbreak over stripped-down production
|
pop
|
K-pop solo track celebrating Seoul nightlife with electronic beats and confident delivery
|
k-pop
|
Disco-pop with retro production and empowering lyrics about knowing your worth
|
pop
|
Latin-pop collaboration with reggaeton influences and fierce female empowerment message
|
latin
|
High-energy K-pop with aggressive choreography beats and powerful group chants
|
k-pop
|
Dark R&B with moody production featuring male vocals about toxic attraction
|
r&b
|
80s-influenced synth ballad with emotional vocals about lost love and regret
|
pop
|
Haunting K-pop solo with orchestral production exploring toxic relationships
|
k-pop
|
Flirty pop with cheeky lyrics and retro production about unexpected attraction
|
pop
|
Dreamy pop with Y2K influences and breathy vocals creating nostalgic summer vibes
|
pop
|
Ethereal indie-pop with reverb-heavy production and melancholic vocals about transcendent love
|
indie
|
Atmospheric vintage-pop with cinematic strings and dramatic vocals about fame
|
pop
|
Dreamy indie track with ambient guitars and intimate vocals creating late-night mood
|
indie
|
Dark pop with haunting production and vulnerable vocals about mental health
|
pop
|
Atmospheric British indie-rock with moody guitars and emotional male vocals about crime metaphors
|
indie
|
Upbeat indie-rock with catchy guitars and romantic lyrics about finding perfect match
|
indie
|
Melancholic indie-rock with ambient production exploring complicated relationships
|
indie
|
Smooth R&B with intimate vocals and minimalist production about self-love journey
|
r&b
|
Alternative R&B with trap influences and layered vocals about complicated love
|
r&b
|
Rock anthem with Italian flair mixing aggressive guitars with seductive vocals
|
rock
|
Emotional pop ballad with orchestral arrangement dedicated to someone special
|
pop
|
Feel-good pop with throwback production celebrating natural beauty and confidence
|
pop
|
Uplifting pop with sincere vocals and warm production about unconditional acceptance
|
pop
|
Hard-hitting hip-hop with aggressive flow and heavy bass addressing competition
|
hip-hop
|
Piano ballad with powerful vocals and emotional delivery about lost love
|
pop
|
Inspirational pop with acoustic guitar about overcoming life's challenges
|
pop
|
Soft rock ballad with gentle vocals and romantic lyrics about devotion
|
rock
|
Emotional power ballad with soaring female vocals about overwhelming love
|
pop
|
Orchestral pop ballad with powerful vocals and sweeping production about complete devotion
|
pop
|
Viral indie-pop with unique male vocals and intimate production about double takes
|
indie
|
Bilingual indie-pop with dreamy production and soft vocals creating intimate atmosphere
|
indie
|
Mid-2000s R&B with signature production and smooth vocals about attraction
|
r&b
|
Sultry electronic pop with breathy vocals and dark production about physical desire
|
pop
|
Hyperpop anthem with distorted production and party-ready energy
|
pop
|
Club-ready pop with pulsing beats and confident vocals celebrating success
|
pop
|
Dark R&B with vengeful lyrics and cinematic production inspired by martial arts films
|
r&b
|
Smooth jazz-influenced track with saxophone and groovy bassline creating chill vibes
|
r&b
|
Classic R&B with smooth vocals and timeless production about love's impact
|
r&b
|
Emotional R&B ballad with vulnerable vocals about heartbreak and moving on
|
r&b
|
Korean rock ballad with emotional guitars and powerful vocals about waiting in the rain
|
k-rock
|
Melancholic Korean rock with atmospheric production and emotional delivery about apologies
|
k-rock
|
Classic jazz piano piece with elegant melodies evoking winter scenes in New York
|
jazz
|
Smooth jazz standard with sophisticated arrangement and relaxed tempo
|
jazz
|
Vintage jazz vocal with orchestral backing capturing romantic New England autumn
|
jazz
|
Intimate jazz ballad with soft trumpet and vulnerable male vocals about falling too quickly
|
jazz
|
Classic jazz standard with melancholic trumpet and gentle swing rhythm about seasonal change
|
jazz
|
Cheerful pop with harmonious vocals and optimistic lyrics about feeling on top
|
pop
|
Emotional K-pop ballad with delicate vocals and piano-driven melody about final farewells
|
k-pop
|
Confident K-pop track with powerful choreography beats and self-assured lyrics about being the best
|
k-pop
|
Fierce R&B-pop with attitude-filled vocals and bass-heavy production about confidence
|
r&b
|
Nostalgic hyperpop with glitchy production and autotuned vocals about chasing euphoric moments
|
pop
|
Sultry alternative R&B with smooth vocals and minimalist beats exploring physical attraction
|
r&b
|
Dreamy R&B with ethereal production and layered vocals about the number's significance
|
r&b
|
Upbeat K-pop collaboration with playful vocals and party-ready production asking where you at
|
k-pop
|
Energetic pop-rock with catchy hooks and confident vocals about non-stop conversation
|
pop
|
Bold hip-hop track with fierce female rap and trap beats about dual personalities
|
hip-hop
|
Clever wordplay in alt-hip-hop style with catchy production about avoiding reality
|
hip-hop
|
Moody indie rock with distinctive British vocals about late night drunk calls
|
indie
|
Japanese rock anthem with powerful vocals and driving guitars about rebellion
|
rock
|
Explosive dance-pop with infectious beat and party lyrics about lighting up the night
|
pop
|
Latin-pop fusion with Colombian rhythms and bilingual vocals about truthful body language
|
latin
|
Confident K-pop with Latin influences and fierce choreography celebrating identity
|
k-pop
|
Caribbean-influenced pop with commanding vocals and dancehall beats about bad boys
|
pop
|
Arena rock anthem with thunderous drums and inspirational lyrics about transformation
|
rock
|
Emotional K-rock ballad with heartfelt vocals and guitar-driven melody about past love
|
k-rock
|
Progressive house with country vocals building to euphoric drop about awakening
|
pop
|
K-pop track mixing English and Korean with smooth production about chasing success
|
k-pop
|
Powerful ballad with soaring female vocals and orchestral arrangement about nature
|
pop
|
Uplifting pop-rock with youthful energy and positive message about living fully
|
pop
|
Neo-soul masterpiece with conscious rap and live instrumentation about societal issues
|
r&b
|
Classic 90s R&B with soulful vocals and hip-hop beats defining an era
|
r&b
|
Energetic K-pop with catchy hook and synchronized choreography about attraction
|
k-pop
|
Dreamy K-pop with minimalist R&B production and soft vocals creating chill vibes
|
k-pop
|
Fierce hip-hop anthem with confident female rap and trap production about success
|
hip-hop
|
West Coast hip-hop with smooth flow and G-funk production about lifestyle
|
hip-hop
|
Conscious hip-hop with introspective lyrics and jazz-influenced beats about growth
|
hip-hop
|
Latin reggaeton with infectious beat and Spanish vocals about dancing all night
|
latin
|
Modern Latin trap with autotuned vocals and heavy bass about heartbreak
|
latin
|
Moody indie rock with jangly guitars and introspective lyrics about youth
|
indie
|
Song Genre Classification Text Dataset
Dataset Summary
Purpose: This dataset was created for multi-class text classification of song descriptions into music genres, developed as part of CMU 24-679 coursework to explore text augmentation techniques in NLP.
Quick Stats:
- 1,122 total samples (102 original + 1,020 augmented)
- 10 genre categories
- ~200 character descriptions per sample
- Balanced augmentation (10x per original)
Contact: [email protected]
Dataset Composition
Features
text: String (song description, ~200 characters)label: String (genre category)
Genre Distribution
| Genre | Original | Augmented | Percentage |
|---|---|---|---|
| pop | 35 | 350 | 34.3% |
| k-pop | 15 | 150 | 14.7% |
| r&b | 15 | 150 | 14.7% |
| indie | 10 | 100 | 9.8% |
| rock | 8 | 80 | 7.8% |
| hip-hop | 7 | 70 | 6.9% |
| jazz | 5 | 50 | 4.9% |
| c-pop | 4 | 40 | 3.9% |
| latin | 4 | 40 | 3.9% |
| k-rock | 3 | 30 | 2.9% |
Data Splits
- original: 102 manually written song descriptions
- augmented: 1,020 synthetically augmented descriptions (10x augmentation per original)
Data Collection Process
Collection Methodology
Song descriptions created between January-February 2025:
- Based on 100+ popular songs from various streaming platforms
- Covers music from 1980s-2020s
- International representation (English, Korean, Chinese, Spanish)
- Manual description writing without using copyrighted lyrics
Selection Criteria
- Popular/recognizable songs across genres
- Diverse cultural and temporal representation
- Clear genre categorization
- No explicit content or offensive material
Preprocessing and Augmentation
Preprocessing Pipeline
- Standardized to ~200 character descriptions
- Removed artist names and song titles from text
- Ensured grammatical consistency
- Verified genre labels
Augmentation Techniques
Each original generated 10 augmented variants using:
- EDA: Synonym replacement, random deletion/swap/insertion (3 variants)
- Character Noise: Random drops and swaps (3 variants)
- Back-Translation: English → German → English pipeline (1 variant)
- T5 Paraphrasing: Neural text generation with T5-small (1 variant)
- Combined: EDA + character noise (2 variants)
Labels and Annotation
Labeling Schema
- pop: Mainstream pop music
- k-pop: Korean pop music
- r&b: Rhythm and blues
- indie: Independent/alternative
- rock: Rock and soft rock
- hip-hop: Rap and hip-hop
- jazz: Jazz standards
- c-pop: Chinese pop music
- latin: Latin/Spanish music
- k-rock: Korean rock
Annotation Process
- Manual labeling based on known genre classifications
- Single-label assignment (no multi-genre)
- Verified against music platform categorizations
Intended Use and Limitations
Intended Use Cases
- Text classification model training
- Studying text augmentation effectiveness
- NLP educational projects
- Genre classification research baseline
Limitations
- Limited to ~200 character descriptions
- Subjective genre boundaries
- Western music bias despite international songs
- Augmented samples may contain grammatical errors
- Small original dataset size (102 samples)
Out-of-Scope Uses
- Production music recommendation systems
- Detailed music analysis (lyrics, audio)
- Multi-label genre classification
- Commercial applications without additional data
Ethical Considerations
Representation
- Attempted balance across major global music markets
- Acknowledges genre classification subjectivity
- May not equally represent all music communities
Privacy
- No personal information included
- No copyrighted lyrics reproduced
- Descriptions are original creations
Cultural Sensitivity
- Genre labels may oversimplify cultural music traditions
- "World music" avoided as a category due to its problematic nature
- Users should be aware of Western-centric genre definitions
AI Usage Disclosure
AI-Assisted Components
- Augmentation: Back-translation using Helsinki-NLP models
- Paraphrasing: T5-small model for text generation
- Documentation: README structure refined with AI assistance
- Descriptions: Written with human knowledge, no lyrics copied
Human Oversight
- All original descriptions manually written
- Genre labels manually assigned and verified
- Augmentation quality manually reviewed
- No copyrighted material reproduced
Usage Example
from datasets import load_dataset
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import LogisticRegression
# Load dataset
dataset = load_dataset("maryzhang/hw1-24679-text-dataset-augmented")
# Prepare data
X_train = dataset['augmented']['text']
y_train = dataset['augmented']['label']
X_test = dataset['original']['text']
y_test = dataset['original']['label']
# Train classifier
vectorizer = TfidfVectorizer(max_features=1000)
X_train_vec = vectorizer.fit_transform(X_train)
X_test_vec = vectorizer.transform(X_test)
clf = LogisticRegression()
clf.fit(X_train_vec, y_train)
accuracy = clf.score(X_test_vec, y_test)
print(f"Accuracy: {accuracy:.2f}")
Citation
bibtex@dataset{zhang2025songgenre, author = {Mary Zhang}, title = {Song Genre Classification Text Dataset}, year = {2025}, publisher = {Hugging Face}, note = {CMU 24-679 Homework 1}, url = {https://huggingface.co/datasets/maryzhang/hw1-24679-text-dataset-augmented} }
License
This dataset is released under the MIT License.
Contact
Dataset created by Mary Zhang for CMU 24-679. For questions or issues, please contact [email protected].
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