A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification.

Rémi Uro, David Doukhan, Albert Rilliard, Laetitia Larcher, Anissa-Claire Adgharouamane, Marie Tahon, Antoine Laurent


Abstract
This paper presents a semi-automatic approach to create a diachronic corpus of voices balanced for speaker’s age, gender, and recording period, according to 32 categories (2 genders, 4 age ranges and 4 recording periods). Corpora were selected at French National Institute of Audiovisual (INA) to obtain at least 30 speakers per category (a total of 960 speakers; only 874 have be found yet). For each speaker, speech excerpts were extracted from audiovisual documents using an automatic pipeline consisting of speech detection, background music and overlapped speech removal and speaker diarization, used to present clean speaker segments to human annotators identifying target speakers. This pipeline proved highly effective, cutting down manual processing by a factor of ten. Evaluation of the quality of the automatic processing and of the final output is provided. It shows the automatic processing compare to up-to-date process, and that the output provides high quality speech for most of the selected excerpts. This method is thus recommendable for creating large corpora of known target speakers.
Anthology ID:
2022.lrec-1.350
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
3271–3280
Language:
URL:
https://aclanthology.org/2022.lrec-1.350
DOI:
Bibkey:
Cite (ACL):
Rémi Uro, David Doukhan, Albert Rilliard, Laetitia Larcher, Anissa-Claire Adgharouamane, Marie Tahon, and Antoine Laurent. 2022. A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification.. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 3271–3280, Marseille, France. European Language Resources Association.
Cite (Informal):
A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification. (Uro et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.350.pdf
Data
DIHARD II