Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Zajíc, Zbyněk | |
| dc.contributor.author | Kunešová, Marie | |
| dc.contributor.author | Müller, Luděk | |
| dc.date.accessioned | 2022-03-28T10:00:28Z | - |
| dc.date.available | 2022-03-28T10:00:28Z | - |
| dc.date.issued | 2021 | |
| dc.identifier.citation | ZAJÍC, Z. KUNEŠOVÁ, M. MÜLLER, L. Applying EEND Diarization to Telephone Recordings from a Call Center. In 23rd International Conference, SPECOM 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings. Cham: Springer, 2021. s. 807-817. ISBN: 978-3-030-87801-6 , ISSN: 0302-9743 | cs |
| dc.identifier.isbn | 978-3-030-87801-6 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | 2-s2.0-85116359179 | |
| dc.identifier.uri | http://hdl.handle.net/11025/47255 | |
| dc.format | 11 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Springer | en |
| dc.relation.ispartofseries | 23rd International Conference, SPECOM 2021, St. Petersburg, Russia, September 27–30, 2021, Proceedings | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © Springer | en |
| dc.title | Applying EEND Diarization to Telephone Recordings from a Call Center | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | ConferenceObject | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | In this paper, we focus on the issue of speaker diarization of data from a real call center. We have previously proposed a specialized solution to the problem, which employed additional knowledge about the identities of the phone operators (in our case, the language counselors from the Language Consulting Center), thus improving performance over the baseline. But a recent end-to-end diarization method, EEND, has since proven very successful on other data and was shown to surpass the previous state of the art in the field. Thus, we chose to compare this new method with our own previous approach. Using an existing implementation of the EEND method (adapted using a small amount of the target data from the Language Consulting Center), we successfully surpass the performance of our previous approach (17.42% vs. 19.39% DER), without the need for any additional information about speaker identities. The majority of the remaining diarization error of the EEND system is due to incorrect decisions between speech and silence, rather than speaker confusion. For comparison, we also show the results of a more standard diarization approach, represented by the method used in the Kaldi toolkit. | en |
| dc.subject.translated | Diarization | en |
| dc.subject.translated | End-to-end | en |
| dc.subject.translated | X-vector | en |
| dc.subject.translated | EEND | en |
| dc.identifier.doi | 10.1007/978-3-030-87802-3_72 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.obd | 43933458 | |
| dc.project.ID | LM2018101/LINDAT/CLARIAH-CZ – Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy | cs |
| dc.project.ID | 90042/Velká výzkumná infrastruktura povinnost (J) - CESNET II | cs |
| Vyskytuje se v kolekcích: | Konferenční příspěvky / Conference Papers (KKY) OBD | |
Soubory připojené k záznamu:
| Soubor | Velikost | Formát | |
|---|---|---|---|
| Zajíc2021_Chapter_ApplyingEENDDiarizationToTelep.pdf | 377,54 kB | Adobe PDF | Zobrazit/otevřít Vyžádat kopii |
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