Detail publikačního výsledku

Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio

ZHANG, L.; WANG, X.; COOPER, E.; DIEZ SÁNCHEZ, M.; LANDINI, F.; EVANS, N.; YAMAGISHI, J.

Originální název

Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio

Anglický název

Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This paper defines Spoof Diarization as a novel task in the Partial Spoof (PS) scenario. It aims to determine what spoofed when, which includes not only locating spoof regions but also clustering them according to different spoofing methods. As a pioneering study in spoof diarization, we focus on defining the task, establishing evaluation metrics, and proposing a bench- mark model, namely the Countermeasure-Condition Cluster- ing (3C) model. Utilizing this model, we first explore how to effectively train countermeasures to support spoof diariza- tion using three labeling schemes. We then utilize spoof lo- calization predictions to enhance the diarization performance. This first study reveals the high complexity of the task, even in restricted scenarios where only a single speaker per au- dio file and an oracle number of spoofing methods are con- sidered. Our code is available at https://github.com/ nii-yamagishilab/PartialSpoof.

Anglický abstrakt

This paper defines Spoof Diarization as a novel task in the Partial Spoof (PS) scenario. It aims to determine what spoofed when, which includes not only locating spoof regions but also clustering them according to different spoofing methods. As a pioneering study in spoof diarization, we focus on defining the task, establishing evaluation metrics, and proposing a bench- mark model, namely the Countermeasure-Condition Cluster- ing (3C) model. Utilizing this model, we first explore how to effectively train countermeasures to support spoof diariza- tion using three labeling schemes. We then utilize spoof lo- calization predictions to enhance the diarization performance. This first study reveals the high complexity of the task, even in restricted scenarios where only a single speaker per au- dio file and an oracle number of spoofing methods are con- sidered. Our code is available at https://github.com/ nii-yamagishilab/PartialSpoof.

Klíčová slova

partial spoof, spoof diarization, countermeasure, clustering

Klíčová slova v angličtině

partial spoof, spoof diarization, countermeasure, clustering

Autoři

ZHANG, L.; WANG, X.; COOPER, E.; DIEZ SÁNCHEZ, M.; LANDINI, F.; EVANS, N.; YAMAGISHI, J.

Rok RIV

2025

Vydáno

01.09.2024

Nakladatel

International Speech Communication Association

Místo

Kos

Kniha

Proceedings of Interspeech 2024

ISSN

1990-9772

Periodikum

Proceedings of Interspeech

Svazek

2024

Číslo

9

Stát

Francouzská republika

Strany od

502

Strany do

506

Strany počet

5

URL

https://www.isca-archive.org/interspeech_2024/zhang24j_interspeech.pdf

BibTex

@inproceedings{BUT193676,
  author="ZHANG, L. and WANG, X. and COOPER, E. and DIEZ SÁNCHEZ, M. and LANDINI, F. and EVANS, N. and YAMAGISHI, J.",
  title="Spoof Diarization: {"}What Spoofed When{"} in Partially Spoofed Audio",
  booktitle="Proceedings of Interspeech 2024",
  year="2024",
  journal="Proceedings of Interspeech",
  volume="2024",
  number="9",
  pages="502--506",
  publisher="International Speech Communication Association",
  address="Kos",
  doi="10.21437/Interspeech.2024-1365",
  issn="1990-9772",
  url="https://www.isca-archive.org/interspeech_2024/zhang24j_interspeech.pdf"
}

Dokumenty

zhang_2024j_interspeech