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LANDINI, F. LOZANO DÍEZ, A. DIEZ SÁNCHEZ, M. BURGET, L.
Originální název
From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
End-to-end neural diarization (EEND) is nowadays one of the most prominent research topics in speaker diarization. EEND presents an attractive alternative to standard cascaded diarization systems since a single system is trained at once to deal with the whole diarization problem. Several EEND variants and approaches are being proposed, however, all these models require large amounts of annotated data for training but available annotated data are scarce. Thus, EEND works have used mostly simulated mixtures for training. However, simulated mixtures do not resemble real conversations in many aspects. In this work we present an alternative method for creating synthetic conversations that resemble real ones by using statistics about distributions of pauses and overlaps estimated on genuine conversations. Furthermore, we analyze the effect of the source of the statistics, different augmentations and amounts of data. We demonstrate that our approach performs substantially better than the original one, while reducing the dependence on the fine-tuning stage. Experiments are carried out on 2-speaker telephone conversations of Callhome and DIHARD 3. Together with this publication, we release our implementations of EEND and the method for creating simulated conversations.
Klíčová slova
peaker diarization, end-to-end neural diariza- tion, simulated conversations
Autoři
LANDINI, F.; LOZANO DÍEZ, A.; DIEZ SÁNCHEZ, M.; BURGET, L.
Vydáno
18. 9. 2022
Nakladatel
International Speech Communication Association
Místo
Incheon
ISSN
1990-9772
Periodikum
Proceedings of Interspeech
Ročník
2022
Číslo
9
Stát
Francouzská republika
Strany od
5095
Strany do
5099
Strany počet
5
URL
https://www.isca-speech.org/archive/pdfs/interspeech_2022/landini22_interspeech.pdf
BibTex
@inproceedings{BUT179780, author="Federico Nicolás {Landini} and Alicia {Lozano Díez} and Mireia {Diez Sánchez} and Lukáš {Burget}", title="From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization", booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH", year="2022", journal="Proceedings of Interspeech", volume="2022", number="9", pages="5095--5099", publisher="International Speech Communication Association", address="Incheon", doi="10.21437/Interspeech.2022-10451", issn="1990-9772", url="https://www.isca-speech.org/archive/pdfs/interspeech_2022/landini22_interspeech.pdf" }