ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification

Bergler C, Schmitt M, Maier A, Symonds H, Spong P, Ness S, Tzanetakis G, Nöth E (2021)

Publication Type: Conference contribution, Original article

Publication year: 2021

Publisher: International Speech Communication Association

Conference Proceedings Title: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2021

Event location: Brno, Czechia

DOI: 10.21437/Interspeech.2021-616

Authors with CRIS profile

Christian Bergler Lehrstuhl für Informatik 5 (Mustererkennung) Andreas Maier Lehrstuhl für Informatik 5 (Mustererkennung) Elmar Nöth Professur für Informatik (Mustererkennung)

Related research project(s)

Deep Learning Applied to Animal Linguistics (DeepAL) April 1, 2018 - April 1, 2022

How to cite

APA:

Bergler, C., Schmitt, M., Maier, A., Symonds, H., Spong, P., Ness, S.,... Nöth, E. (2021). ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2021. Brno, Czechia: International Speech Communication Association.

MLA:

Bergler, Christian, et al. "ORCA-SLANG: An Automatic Multi-Stage Semi-Supervised Deep Learning Framework for Large-Scale Killer Whale Call Type Identification." Proceedings of the 22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021, Brno, Czechia International Speech Communication Association, 2021.

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