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Fretting-Transformer: Encoder-Decoder Model for MIDI to Tablature Transcription

Hamberger, Anna ; Murgul, Sebastian ORCID iD icon 1; Schmidt, Jochen; Heizmann, Michael 1
1 Institut für Industrielle Informationstechnik (IIIT), Karlsruher Institut für Technologie (KIT)

Abstract:

Music transcription plays a pivotal role in Music Infor-
mation Retrieval (MIR), particularly for stringed instru-
ments like the guitar, where symbolic music notations such
as MIDI lack crucial playability information. This con-
tribution introduces the Fretting-Transformer, an encoder-
decoder model that utilizes a T5 transformer architecture to
automate the transcription of MIDI sequences into guitar
tablature. By framing the task as a symbolic translation
problem, the model addresses key challenges, including
string-fret ambiguity and physical playability. The pro-
posed system leverages diverse datasets, including DadaGP,
GuitarToday, and Leduc, with novel data pre-processing
and tokenization strategies. We have developed metrics for
tablature accuracy and playability to quantitatively evalu-
ate the performance. The experimental results demonstrate
that the Fretting-Transformer surpasses baseline methods
like A∗ and commercial applications like Guitar Pro. The
integration of context-sensitive processing and tuning/capo
conditioning further enhances the model’s performance,
laying a robust foundation for future developments in auto-
... mehr


Postprint §
DOI: 10.5445/IR/1000183783
Veröffentlicht am 05.08.2025
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industrielle Informationstechnik (IIIT)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 06.2025
Sprache Englisch
Identifikator ISBN: 978-1-951748-00-5
KITopen-ID: 1000183783
Erschienen in Proceedings of the 50th International Computer Music Conference, Boston from June 8 – 14, 2025
Veranstaltung 50th International Computer Music Conference (ICMC 2025), Boston, MA, USA, 08.06.2025 – 14.06.2025
Verlag Composers Society of Singapore
Seiten 438-445
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