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How would it sounds, if we could hear all seismically generated signals within the Earth?
How can the analysis of seismic signals benefit from Music Information Retrieval (MIR) research?
How can the analysis of Traditional Georgian Vocal Music benefit from seismologically inspired recordings techniques?
How can geographic concepts help to visualize the chord progressions in Traditional Georgian Vocal Music?
What can we learn from heartbeat recordings during phonation?
Soundscape Earth

Everything that vibrates sounds, even if we can not hear it with our ears.

MIR beyond music

The similarity of musical and seismic signal properties can be exploited during analysis.

Singing and body vibrations

Body vibration recordings allow the separate analysis of individual singers in an ensemble.

Chordscapes and song trajectories

Graph theory provides powerful tools to investigate the chord progression structure in music.

Beyond Acoustics

Heartbeat variability recordings during singing may capture non-verbal interaction of singers.

  • SeismoSoundScape-Lab

Computational Analysis of Traditional Georgian Vocal Music: The GVM Project

Within the GVM project [DFG MU 2686/13-1, SCHE 280/20-1], we apply computational methods from audio signal processing and music information retrieval (MIR) to study traditional Georgian vocal music.

The GVM dataset

In preparation for the GVM project, extensive fieldwork was conducted in Georgia (with focus on Svaneti) to collect a set of multi-media recordings of traditional Georgian vocal music for analysis.

Impressions from the 2019 Achara fieldwork

Impressions From Achara

During the summer of 2019, we conducted field work in Achara and Guria. In addition to lots of new recordings, we came back with unforgettable impressions, some of which we’d like to share here.

Khelkhvavi from Ozurgeti

Singing From Heart to Heart

Together with the ensemble Khelkhvavi from Ozurgeti, we conducted an experiment to monitor the synchronization of the singers' heartbeat rates while they performed the Gurian song Chven Mshvidoba.

GVM-Interface

From Oral Tradition to Online Access

We explore new ways of engaging with traditional Georgian vocal music using computational approaches and web-based interfaces.

Artem Erkomaishvili

The Heritage of Artem Erkomaishvili

The Tbilisi State Conservatory recordings of Artem Erkomaishvili from 1966 are not only a cultural treasure but also an extremely valuable source of information regarding prior performance practice.

Svan funeralsingers in the village of Latali.

Searching For The Sources Of Georgian Polyphony

Because of their roots in very old, possibly pre-christian traditions, Svan funeral songs Zär, can possibly tell us something about the early layers of Georgian musical thinking.

Song Paths In Chordscapes

Representing chords in a song as vertices in a directed graphs allows to illustrate songs as paths in a chordscape to analyse the structure of the music.

Beyond Score Representations

Pitch trajectories calculated from larynx microphone recordings pave the way for new representations of traditional Georgian songs.

The Quintina

Real time analysis and display of larynx microphone recordings helps to unravel the mysteries of the Quintina, when the four singers of the Sardinian group Concordu Lussurzesu produce five voices.

Map of recorded body vibrations during singing

Straight From The Larynx

Recordings of body vibration during singing changes ethnomusicological field recording practice. Individual voices can be recorded jointly, but analysed separately.

20 Years Inner Earth

20 Years Inner Earth

The year 2019 is the 20th anniversary of the release of the award winning CD Inner Earth: a seismosonic symphony in which Wolfgang Loos and Frank Scherbaum captured the sound of our home planet.

Papers & Presentations (2020 - 2023)

Scherbaum, F., Rosenzweig, S., Dokht Dolatabadi Esfahani, R., Mzhavanadze, N., Schwär, S., Müller, M.  (2023). Novel Representations of Traditional Georgian Vocal Music in Times of Online Access. To appear in „Georgian Traditional Polyphony - Modern Trends and Development Perspectives“, Ed. Rusudan Tsurtsumia and Giorgi Donadze. (PDF)

Arom, S.,  Caron-Darras, F., Kane, F., Lolashvili, A. & Scherbaum, F. (2022). Categorization of chord inventories and chord progressions of Georgian polyphony. 11. International Symposium on Traditional Polyphony, Tbilisi, 26- 30 September 2022, Tbilisi, Georgia. (For backup purposes pre-recorded Video of the actual presentation  in Tbilisi, which differs only slightly from this version.)

Scherbaum,  F. (2022). Five Years of Computational Analysis of Traditional Georgian Vocal Music: the GVM project. 11. International Symposium on Traditional Polyphony, Tbilisi, 26- 30 September 2022, Tbilisi, Georgia. (For backup purposes pre-recorded Video of the actual presentation  in Tbilisi, which differs only slightly from this version.)

Scherbaum, F., & Müller, M. (2022). Togetherness in Traditional Georgian Singing: From Tuning Adjustments to Synchronisation of Heartbeat Variability. Presentation at the Musical Togetherness Symposium (MTS-22), 13-15 July 2022, mdw – University of Music and Performing Arts Vienna, Vienna (Austria). (Video)

Scherbaum, F., & Müller, M. (2022). From Intonation Adjustments to Synchronisation of Heart Beat Variability: Singer Interaction in Traditional Georgian Vocal Music. submitted to Musicologist 2022/07/18. (PDF)

Scherbaum, F., Mzhavanadze, N., Rosenzweig, S., & Müller, M. (2022). Tuning Systems of Traditional Georgian Singing Determined From a New Corpus of  Field Recordings. Musicologist 2022. 6 (2): 142-168. DOI: 10.33906/musicologist.1068947 (PDF)

Rosenzweig, S., Scherbaum, F., Müller, M. (2022). Computer-assisted analysis of field recordings: A case study of Georgian funeral songs. J. Comput. Cult. Herit. 16, 1, Article 13 (December 2022), 16 pages. doi.org/10.1145/3551645 (

PDF)

Mzhavanadze, N. , Scherbaum, F. (2021). Svan Funeral Dirges (Zär): Cultural Context. Musicologist, 5 (2), 133-165, DOI: 10.33906/musicologist.906765. (PDF)

Scherbaum, F , Mzhavanadze, N . (2021). Svan Funeral Dirges (Zär): Language-Music Relation and Phonetic Properties . Musicologist , 5 (1) , 67-82 .  (PDF)

Zali, Z., M. Ohrnberger, F. Scherbaum, F. Cotton, and E. P. S. Eibl (2021). Volcanic Tremor Extraction and Earthquake Detection Using Music Information Retrieval Algorithms, Seismol. Res. Lett. 92, 3668–3681, doi: 10.1785/0220210016  (PDF)

Scherbaum, F., Mzhavanadze, N., Arom, S., Rosenzweig, S., & Müller, M., Analysis of Tonal Organisation and Intonation Practice in the Tbilisi State Conservatory Recordings of Artem Erkomaishvili of 1966, Presented at the 6th International Conference on Analytical Approaches to World Music, 12 June 2021 in the Special Session in Honor of Simha Arom (Video).

Rosenzweig, S., Scherbaum, F., & Müller, M. (2021). Reliability assessment of singing voice F0-estimates using multiple algorithms. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP): 261–265, 2021. (PDF)

Scherbaum, F.  & Mzhavanadze, N. (2020). Svan Funeral Dirges (Zär): Musical Acoustical Analysis of a New Collection of Field Recordings, Musicologist, 4, 2, 138-167, DOI: 10.33906/musicologist.782094. (PDF)

Mzhavanadze, N. & F. Scherbaum, (2020). Svan Funeral Dirges (Zär): Musicological Analysis, Musicologist, 4, 2, 168-197, DOI: 10.33906/musicologist.782185. (PDF)

Mzhavanadze, N. & F. Scherbaum (2020), Zär, polyphonic group laments from Svaneti/Georgia, Video presentation at the Annual Meeting of the Society of Ethnomusicology, Ottawa, 2020 Oct 30. (Video)

Scherbaum, F., Mzhavanadze, N., Arom, S., Rosenzweig, S., and  Müller, M. (2020). Tonal Organization of the Erkomaishvili Dataset: Pitches, Scales, Melodies and Harmonies.  Computational Analysis Of Traditional Georgian Vocal Music, 1, 64 pp., doi.org/10.25932/publishup-47614. (

PDF)

Rosenzweig, S., Cuesta, H., Weiß, C., Scherbaum, F., Gómez, E., & Müller, M. (2020). Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing. Transactions of the International Society for Music Information Retrieval, 3(1), pp. 98–110. DOI: https://doi.org/10.5334/tismir.48 (PDF)

 

Rosenzweig, S., Scherbaum, F., Shugliashvili, D., Arifi-Müller, V., & Müller, M. (2020). Erkomaishvili Dataset: A Curated Corpus of Traditional Georgian Vocal Music for Computational Musicology. Transactions of the International Society for Music Information Retrieval, 3(1), pp. 31–41. DOI: doi.org/10.5334/tismir.44, Zenodo DOI:

https://doi.org/10.5281/zenodo.6900389 (PDF)