108424 20230519145502.0 doi 10.3390/app11188521 sideral 124900 ART-2021-124900 eng Viñals, Ignacio Universidad de Zaragoza (orcid)0000-0001-9137-4013 The Domain Mismatch Problem in the Broadcast Speaker Attribution Task 2021 Access copy available to the general public Unrestricted The demand of high-quality metadata for the available multimedia content requires the development of new techniques able to correctly identify more and more information, including the speaker information. The task known as speaker attribution aims at identifying all or part of the speakers in the audio under analysis. In this work, we carry out a study of the speaker attribution problem in the broadcast domain. Through our experiments, we illustrate the positive impact of diarization on the final performance. Additionally, we show the influence of the variability present in broadcast data, depicting the broadcast domain as a collection of subdomains with particular characteristics. Taking these two factors into account, we also propose alternative approximations robust against domain mismatch. These approximations include a semisupervised alternative as well as a totally unsupervised new hybrid solution fusing diarization and speaker assignment. Thanks to these two approximations, our performance is boosted around a relative 50%. The analysis has been carried out using the corpus for the Albayzín 2020 challenge, a diarization and speaker attribution evaluation working with broadcast data. These data, provided by Radio Televisión Española (RTVE), the Spanish public Radio and TV Corporation, include multiple shows and genres to analyze the impact of new speech technologies in real-world scenarios. info:eu-repo/grantAgreement/ES/DGA/T36-20R info:eu-repo/grantAgreement/EC/H2020/101007666/EU/Exchanges for SPEech ReseArch aNd TechnOlogies/ESPERANTO This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 101007666-ESPERANTO info:eu-repo/grantAgreement/ES/MINECO/TIN2017-85854-C4-1-R info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 2.838 2021 ENGINEERING, MULTIDISCIPLINARY 39 / 92 = 0.424 2021 Q2 T2 PHYSICS, APPLIED 76 / 161 = 0.472 2021 Q2 T2 MATERIALS SCIENCE, MULTIDISCIPLINARY 218 / 345 = 0.632 2021 Q3 T2 CHEMISTRY, MULTIDISCIPLINARY 100 / 180 = 0.556 2021 Q3 T2 0.507 2021 Engineering (miscellaneous) 2021 Q2 Computer Science Applications 2021 Q2 Process Chemistry and Technology 2021 Q2 Materials Science (miscellaneous) 2021 Q2 Fluid Flow and Transfer Processes 2021 Q2 3.7 2021 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Ortega, Alfonso Universidad de Zaragoza (orcid)0000-0001-5803-4316 Miguel, Antonio Universidad de Zaragoza (orcid)0000-0002-3886-7748 Lleida, Eduardo Universidad de Zaragoza (orcid)0000-0003-1772-0605 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 11, 18 (2021), 8521 [19 p.] Appl. sci. Applied Sciences (Switzerland) 2076-3417 11068684 http://zaguan.unizar.es/record/108424/files/texto_completo.pdf Versión publicada 2696132 http://zaguan.unizar.es/record/108424/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:108424 articulos driver 2023-05-18-15:01:16 ARTICLE