Pushkar Gautam, B.Tech CSE AIML, 2nd Year, 3rd Semester, LNCT University, Bhopal
Abstract
This study explores the integration of artificial intelligence (AI) with human creative skills to produce music based on classical Hindi literary meters, known as chhands. Using Suno.AI, approximately 25 AI-generated songs were created, leveraging structured poetic frameworks and retaining full commercial rights. The research evaluates the effectiveness of AI in capturing emotional depth, the role of traditional poetic structures in enhancing output quality, and the potential for monetization across national and international platforms. The findings highlight that AI-human collaboration significantly amplifies creative potential, while also revealing platform restrictions that limit AI-generated content distribution.
1. Introduction
The intersection of AI and creativity offers new avenues for artistic expression. While AI-generated content is increasingly common, its integration with traditional cultural frameworks—such as Hindi chhands—remains largely unexplored. This study investigates how AI can be used collaboratively with human expertise to produce music that retains cultural authenticity, emotional depth, and commercial viability.
2. Objectives
To explore the effectiveness of AI in music composition using structured poetic frameworks.
To evaluate the differences between AI outputs generated with and without adherence to Hindi chhand metrics.
To assess the commercial and social potential of AI-generated music across major distribution platforms.
3. Methodology
Song Creation: 25 original songs were written and owned by the researcher.
AI Collaboration: Suno.AI was used to generate AI versions of these songs. Inputs were structured using classical Hindi chhands to maintain meter, rhyme, and rhythm.
Evaluation: Feedback was collected from college professors, peers, and friends to assess emotional impact and musical quality.
Distribution: Final songs were distributed on Spotify, Amazon Music, and YouTube Music, with commercial rights secured through a premium subscription on Suno.AI.
Comparison: AI-generated songs using unstructured descriptive inputs were compared against those using chhand-based inputs to evaluate qualitative differences.
4. Results
Enhanced Output Quality: Songs structured with chhands had greater emotional resonance and musical coherence compared to unstructured AI-generated outputs.
Voice Integration: Suno.AI successfully matched male and female voices to the musical structure, producing high-quality auditory results.
Commercialization: Securing commercial rights allowed effective monetization on multiple platforms.
Limitations: Platform restrictions (YouTube Content ID, Instagram, WhatsApp) limited the distribution of AI-generated content, highlighting a need for policy adaptation.
*5. Discussion
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The study demonstrates that AI alone cannot fully replicate the nuanced calculations of classical Hindi chhand metrics. Human expertise in structuring these inputs is critical to achieving high-quality, emotionally resonant music. This underscores a broader principle: AI-human collaboration, rather than AI autonomy, maximizes creative outcomes.
The limitations imposed by current content platforms point to a gap between technological capabilities and regulatory frameworks. Allowing AI-generated content with verified human oversight could unlock significant cultural and commercial opportunities.
*6. Conclusion
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AI can significantly enhance creative productivity when guided by human expertise, particularly in culturally rich domains like Hindi music and literature. This study validates that structured AI-human collaboration produces superior outputs, retains commercial value, and has potential for social impact. Future research should explore scalable frameworks for AI-assisted creative production and advocate for platform policies that enable broader dissemination of AI-generated content.
Keywords:
Artificial Intelligence, Music Production, Hindi Chhands, AI-Human Collaboration, Creative Technology, Commercial Rights.
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