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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Automatic Detection of Speech Sound Disorder in Child Speech Using Posterior-based Speaker Representations ... Ng, Si-Ioi; Ng, Cymie Wing-Yee; Wang, Jiarui. - : arXiv, 2022 BASE Show details 2 Acoustical Analysis of Speech Under Physical Stress in Relation to Physical Activities and Physical Literacy ... Ng, Si-Ioi; Ma, Rui-Si; Lee, Tan. - : arXiv, 2021 BASE Show details 3 Automatic Detection of Phonological Errors in Child Speech Using Siamese Recurrent Autoencoder ... Ng, Si-Ioi; Lee, Tan. - : arXiv, 2020 BASE Show details 4 CUCHILD: A Large-Scale Cantonese Corpus of Child Speech for Phonology and Articulation Assessment ... Ng, Si-Ioi; Ng, Cymie Wing-Yee; Wang, Jiarui; Lee, Tan; Lee, Kathy Yuet-Sheung; Tong, Michael Chi-Fai. - : arXiv, 2020 Abstract: This paper describes the design and development of CUCHILD, a large-scale Cantonese corpus of child speech. The corpus contains spoken words collected from 1,986 child speakers aged from 3 to 6 years old. The speech materials include 130 words of 1 to 4 syllables in length. The speakers cover both typically developing (TD) children and children with speech disorder. The intended use of the corpus is to support scientific and clinical research, as well as technology development related to child speech assessment. The design of the corpus, including selection of words, participants recruitment, data acquisition process, and data pre-processing are described in detail. The results of acoustical analysis are presented to illustrate the properties of child speech. Potential applications of the corpus in automatic speech recognition, phonological error detection and speaker diarization are also discussed. ... : Accepted to INTERSPEECH 2020, Shanghai, China ... Keyword: Audio and Speech Processing eess.AS; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Sound cs.SD URL: https://dx.doi.org/10.48550/arxiv.2008.03188 https://arxiv.org/abs/2008.03188 BASE Hide details

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