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Long-Form Text-to-Music Generation with Adaptive Prompts: A Case of Study in Tabletop Role-Playing Games Soundtracks

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Title: Long-Form Text-to-Music Generation with Adaptive Prompts: A Case of Study in Tabletop Role-Playing Games Soundtracks
Authors: Marra, Felipe, Ferreira, Lucas N.
Publication Year: 2024
Collection: Computer Science
Subject Terms: Computer Science - Sound, Computer Science - Artificial Intelligence, Computer Science - Multimedia, Computer Science - Neural and Evolutionary Computing, Electrical Engineering and Systems Science - Audio and Speech Processing
More Details: This paper investigates the capabilities of text-to-audio music generation models in producing long-form music with prompts that change over time, focusing on soundtrack generation for Tabletop Role-Playing Games (TRPGs). We introduce Babel Bardo, a system that uses Large Language Models (LLMs) to transform speech transcriptions into music descriptions for controlling a text-to-music model. Four versions of Babel Bardo were compared in two TRPG campaigns: a baseline using direct speech transcriptions, and three LLM-based versions with varying approaches to music description generation. Evaluations considered audio quality, story alignment, and transition smoothness. Results indicate that detailed music descriptions improve audio quality while maintaining consistency across consecutive descriptions enhances story alignment and transition smoothness.
Comment: Paper accepted at the LAMIR 2024 workshop
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2411.03948
Accession Number: edsarx.2411.03948
Database: arXiv
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  Data: Long-Form Text-to-Music Generation with Adaptive Prompts: A Case of Study in Tabletop Role-Playing Games Soundtracks
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  Data: <searchLink fieldCode="AR" term="%22Marra%2C+Felipe%22">Marra, Felipe</searchLink><br /><searchLink fieldCode="AR" term="%22Ferreira%2C+Lucas+N%2E%22">Ferreira, Lucas N.</searchLink>
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  Data: 2024
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  Data: Computer Science
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  Data: <searchLink fieldCode="DE" term="%22Computer+Science+-+Sound%22">Computer Science - Sound</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+-+Artificial+Intelligence%22">Computer Science - Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+-+Multimedia%22">Computer Science - Multimedia</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+-+Neural+and+Evolutionary+Computing%22">Computer Science - Neural and Evolutionary Computing</searchLink><br /><searchLink fieldCode="DE" term="%22Electrical+Engineering+and+Systems+Science+-+Audio+and+Speech+Processing%22">Electrical Engineering and Systems Science - Audio and Speech Processing</searchLink>
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  Label: Description
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  Data: This paper investigates the capabilities of text-to-audio music generation models in producing long-form music with prompts that change over time, focusing on soundtrack generation for Tabletop Role-Playing Games (TRPGs). We introduce Babel Bardo, a system that uses Large Language Models (LLMs) to transform speech transcriptions into music descriptions for controlling a text-to-music model. Four versions of Babel Bardo were compared in two TRPG campaigns: a baseline using direct speech transcriptions, and three LLM-based versions with varying approaches to music description generation. Evaluations considered audio quality, story alignment, and transition smoothness. Results indicate that detailed music descriptions improve audio quality while maintaining consistency across consecutive descriptions enhances story alignment and transition smoothness.<br />Comment: Paper accepted at the LAMIR 2024 workshop
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      – SubjectFull: Computer Science - Sound
        Type: general
      – SubjectFull: Computer Science - Artificial Intelligence
        Type: general
      – SubjectFull: Computer Science - Multimedia
        Type: general
      – SubjectFull: Computer Science - Neural and Evolutionary Computing
        Type: general
      – SubjectFull: Electrical Engineering and Systems Science - Audio and Speech Processing
        Type: general
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      – TitleFull: Long-Form Text-to-Music Generation with Adaptive Prompts: A Case of Study in Tabletop Role-Playing Games Soundtracks
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            NameFull: Marra, Felipe
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            NameFull: Ferreira, Lucas N.
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            – D: 06
              M: 11
              Type: published
              Y: 2024
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