From Text to Tune: An End-to-End AI Pipeline for Automated Music Composition

Abstract: We present an integrated system that generates complete musical compositions from textual inputs. Our approach leverages three distinct pretrained models: a text-to-text generation model to produce song lyrics, a text-to-speech (TTS) model to vocalize the lyrics, and a text-to-audio music generator to synthesize complementary background music. Finally, the system overlays the synthesized voice with the background music to produce a final song. Experimental demonstrations indicate that this modular pipeline can generate coherent vocal renditions accompanied by music that supports the song’s mood and style. This work highlights a flexible framework that may be extended to a range of creative and interactive music applications

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-05-09
DOI
https://doi.org/10.22214/ijraset.2025.70529
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
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article

From Text to Tune: An End-to-End AI Pipeline for Automated Music Composition

Shivhar Dhulshette
International Journal for Research in Applied Science and Engineering Technology
Music and Audio Processing
article

From Text to Tune: An End-to-End AI Pipeline for Automated Music Composition

Shivhar Dhulshette
article en

Abstract

Abstract: We present an integrated system that generates complete musical compositions from textual inputs. Our approach leverages three distinct pretrained models: a text-to-text generation model to produce song lyrics, a text-to-speech (TTS) model to vocalize the lyrics, and a text-to-audio music generator to synthesize complementary background music. Finally, the system overlays the synthesized voice with the background music to produce a final song. Experimental demonstrations indicate that this modular pipeline can generate coherent vocal renditions accompanied by music that supports the song’s mood and style. This work highlights a flexible framework that may be extended to a range of creative and interactive music applications

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(5)
Openalex Percentile: Top 89%
Music and Audio Processing
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