波兰多通道视听儿童语音数据集双专家符号诊断。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Michal Krecichwost, Zuzanna Miodonska, Agata Sage, Joanna Trzaskalik, Ewa Kwasniok, Pawel Badura
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引用次数: 0

摘要

本文介绍了用于计算机辅助诊断语漏症(lisp)的波兰语儿童语音视听数据集PAVSig。本研究旨在收集不同儿童语言模式中发音者的发音、声学和视觉外观的数据,特别是在符号化方面。数据收集于2021-2023年波兰6所幼儿园和学校对201名4-8岁儿童进行言语和语言治疗检查期间。诊断与数据记录同时进行,包括15通道空间音频信号和说话者口腔区域的双摄像头立体视觉流。数据记录包括51个单词和17个标识集的视听记录,其中包含所有12种波兰语发音以及由两位独立的语言和语言治疗专家提供的相应的语言和语言治疗诊断。我们共有66,781个音视频片段,包括12,830个单词和53,951个音素(12,576个音节)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Polish multichannel audio-visual child speech dataset with double-expert sigmatism diagnosis.

Polish multichannel audio-visual child speech dataset with double-expert sigmatism diagnosis.

Polish multichannel audio-visual child speech dataset with double-expert sigmatism diagnosis.

Polish multichannel audio-visual child speech dataset with double-expert sigmatism diagnosis.

The paper introduces PAVSig: Polish Audio-Visual child speech dataset for computer-aided diagnosis of Sigmatism (lisp). The study aimed to gather data on articulation, acoustics, and visual appearance of the articulators in different child speech patterns, particularly in sigmatism. The data was collected in 2021-2023 in six kindergarten and school facilities in Poland during the speech and language therapy examinations of 201 children aged 4-8. The diagnosis was performed simultaneously with data recording, including 15-channel spatial audio signals and a dual-camera stereovision stream of the speaker's oral region. The data record comprises audiovisual recordings of 51 words and 17 logotomes containing all 12 Polish sibilants and the corresponding speech and language therapy diagnoses from two independent speech and language therapy experts. In total, we share 66,781 audio-video segments, including 12,830 words and 53,951 phonemes (12,576 sibilants).

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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