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Study Project: Automatic Music Transcription (Part 2)
Ulf Krumnack, Ph.D.
Prof. Dr. phil. Kai-Uwe Kühnberger
Yusuf Brima
Veranstaltungstyp: Studienprojekt
TeilnehmerInnen: This is part 2 of the study project, which started in Summer 2024 and ends in Winter 2024/25. There is no plan to extend this project for a third semester. Hence it is not possible for new students to join this course as a study project as that would require a full duration of two semesters., If you are interested, you may join in form of an interdisciplinary course. This would be worth 6 ECTS and run for one semester. Details can be discussed in the first meeting on November 1st.
Beschreibung:
Automatic Music Transcription encompasses the process of translating musical audio into orresponding musical notation, i.e. sheet music, without requiring additional human intervention. The evident value of such a system for purposes ranging from musical education, preservation, performance, and distribution, along with the inherent commercial appeal tied to its utility, has ignited both academic and commercial interest.
With recent advances in sequence-to-sequence learning techniques that in a good part may be attributed to the development of transformer networks, the creation of a complete AMT system appears more feasible than ever since the inception of the field. A successful example of
general-purpose AMT with the help of transformers has already been reported on by Gardner et al. (2022) [https://arxiv.org/abs/2111.03017]. However, the field still offers many unexplored avenues which bare the potential for impactful research, easily accommodated under the umbrella of Cognitive Science.
To participate in this project, some basic knowledge in deep learning is recommended. People with a background in music theory or audio processing, but also deep learners who want to focus on sequence-to-sequence learning and transformers may find this project specifically interesting.
Erstes Treffen:
Freitag, 01.11.2024 10:00 - 12:00
Ort: nicht angegeben
Semester: WiSe 2024/25
Zeiten:Fr. 10:00 - 12:00 (wöchentlich) - Weekly coordination
Leistungsnachweis:
Veranstaltungsnummer:
8.3081
ECTS-Kreditpunkte:
12
Bereichseinordnung:
Veranstaltungen > Cognitive Science > Master-Programm Courses in English > Human Sciences (e.g. Cognitive Science, Psychology)
Ulf Krumnack, Ph.D.
Prof. Dr. phil. Kai-Uwe Kühnberger
Yusuf Brima
Veranstaltungstyp: Studienprojekt
TeilnehmerInnen: This is part 2 of the study project, which started in Summer 2024 and ends in Winter 2024/25. There is no plan to extend this project for a third semester. Hence it is not possible for new students to join this course as a study project as that would require a full duration of two semesters., If you are interested, you may join in form of an interdisciplinary course. This would be worth 6 ECTS and run for one semester. Details can be discussed in the first meeting on November 1st.
Beschreibung:
Automatic Music Transcription encompasses the process of translating musical audio into orresponding musical notation, i.e. sheet music, without requiring additional human intervention. The evident value of such a system for purposes ranging from musical education, preservation, performance, and distribution, along with the inherent commercial appeal tied to its utility, has ignited both academic and commercial interest.
With recent advances in sequence-to-sequence learning techniques that in a good part may be attributed to the development of transformer networks, the creation of a complete AMT system appears more feasible than ever since the inception of the field. A successful example of
general-purpose AMT with the help of transformers has already been reported on by Gardner et al. (2022) [https://arxiv.org/abs/2111.03017]. However, the field still offers many unexplored avenues which bare the potential for impactful research, easily accommodated under the umbrella of Cognitive Science.
To participate in this project, some basic knowledge in deep learning is recommended. People with a background in music theory or audio processing, but also deep learners who want to focus on sequence-to-sequence learning and transformers may find this project specifically interesting.
Erstes Treffen:
Freitag, 01.11.2024 10:00 - 12:00
Ort: nicht angegeben
Semester: WiSe 2024/25
Zeiten:Fr. 10:00 - 12:00 (wöchentlich) - Weekly coordination
Leistungsnachweis:
Veranstaltungsnummer:
8.3081
ECTS-Kreditpunkte:
12
Bereichseinordnung:
Veranstaltungen > Cognitive Science > Master-Programm Courses in English > Human Sciences (e.g. Cognitive Science, Psychology)
