  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 shows promise for creating large corpora
of known target speakers.
