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 shows promise for creating large corpora of known target speakers.
Abstract (translated)
本文提出了一种半自动化的方法来创建一个平衡说话者年龄、性别和录音周期的语料库。根据32个类别（2个性别，4个年龄范围和4个录音周期），从法国国家视听学院选择了至少30个说话者。对于每个说话者，使用自动管道从音频视频文件中提取演讲片段，该管道包括语音检测、背景音乐和重叠演讲消除以及说话者识别，用于向人类注释者呈现干净的说话者片段。这条管道证明效果显著，将手动处理量降低了十倍。还提供了自动处理和最终输出的质量评估。它表明自动处理与现有过程相比具有优势，并为大多数选定的片段提供了高质量的发音。这种方法具有创建已知目标说话者大型语料库的潜力。
URL
https://arxiv.org/abs/2404.17552
