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本文引用的文献

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Quantifying Velopharyngeal Motion Variation in Speech Sound Production Using an Audio-Informed Dynamic MRI Atlas.使用音频信息动态MRI图谱量化语音发声中的腭咽运动变化。
Proc SPIE Int Soc Opt Eng. 2023 Feb;12464. doi: 10.1117/12.2654082. Epub 2023 Apr 3.
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Tongue Contour Tracking and Segmentation in Lingual Ultrasound for Speech Recognition: A Review.用于语音识别的舌超声中的舌轮廓跟踪与分割:综述
Diagnostics (Basel). 2022 Nov 15;12(11):2811. doi: 10.3390/diagnostics12112811.
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Enhancing linguistic research through 2-mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low-rank reconstruction.通过稀疏时间采样和低秩重建优化的 2 毫米各向同性 3D 动态言语 MRI 增强语言研究。
Magn Reson Med. 2023 Feb;89(2):652-664. doi: 10.1002/mrm.29486. Epub 2022 Oct 26.
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4D magnetic resonance imaging atlas construction using temporally aligned audio waveforms in speech.使用语音中时间对齐的音频波形构建 4D 磁共振成像图谱
J Acoust Soc Am. 2021 Nov;150(5):3500. doi: 10.1121/10.0007064.
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Quantifying Tongue Tip Shape in Apical and Laminal /s/: Contributions of Palate Shape.定量舌尖形状在舌尖和叶音 /s/ 中的表现:腭形的作用。
J Speech Lang Hear Res. 2019 Sep 20;62(9):3149-3159. doi: 10.1044/2019_JSLHR-S-19-0114. Epub 2019 Aug 29.
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Speech Map: A Statistical Multimodal Atlas of 4D Tongue Motion During Speech from Tagged and Cine MR Images.语音图谱:基于标记和电影磁共振成像的语音过程中4D舌运动的统计多模态图谱。
Comput Methods Biomech Biomed Eng Imaging Vis. 2019;7(4):361-373. doi: 10.1080/21681163.2017.1382393. Epub 2017 Oct 9.
7
Atlas-Based Tongue Muscle Correlation Analysis From Tagged and High-Resolution Magnetic Resonance Imaging.基于图谱的舌肌相关性分析:来自标记和高分辨率磁共振成像。
J Speech Lang Hear Res. 2019 Jul 15;62(7):2258-2269. doi: 10.1044/2019_JSLHR-S-18-0495. Epub 2019 Jul 2.
8
The Dynamics of Speech Motor Control Revealed with Time-Resolved fMRI.基于时间分辨 fMRI 的言语运动控制动力学研究。
Cereb Cortex. 2020 Jan 10;30(1):241-255. doi: 10.1093/cercor/bhz084.
9
3D dynamic MRI of the vocal tract during natural speech.自然言语状态下声道的 3D 动态 MRI
Magn Reson Med. 2019 Mar;81(3):1511-1520. doi: 10.1002/mrm.27570. Epub 2018 Nov 3.
10
A Spatio-Temporal Atlas and Statistical Model of the Tongue During Speech from Cine-MRI.基于电影磁共振成像的言语过程中舌头的时空图谱与统计模型
Comput Methods Biomech Biomed Eng Imaging Vis. 2018;6(5):520-531. doi: 10.1080/21681163.2016.1169220. Epub 2016 Apr 28.

量化跨音系环境的发音变化:一种基于图谱的动态磁共振成像方法。

Quantifying articulatory variations across phonological environments: An atlas-based approach using dynamic magnetic resonance imaging.

作者信息

Xing Fangxu, Zhuo Jiachen, Stone Maureen, Liu Xiaofeng, Reese Timothy G, Wedeen Van J, Prince Jerry L, Woo Jonghye

机构信息

Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Boston, Massachusetts 02114, USA.

Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.

出版信息

J Acoust Soc Am. 2024 Dec 1;156(6):4000-4009. doi: 10.1121/10.0034639.

DOI:10.1121/10.0034639
PMID:39670769
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11646136/
Abstract

Identification and quantification of speech variations in velar production across various phonological environments have always been an interesting topic in speech motor control studies. Dynamic magnetic resonance imaging has become a favorable tool for visualizing articulatory deformations and providing quantitative insights into speech activities over time. Based on this modality, it is proposed to employ a workflow of image analysis techniques to uncover potential deformation variations in the human tongue caused by changes in phonological environments by altering the placement of velar consonants in utterances. The speech deformations of four human subjects in three different consonant positions were estimated from magnetic resonance images using a spatiotemporal tracking method before being warped via image registration into a common space-a dynamic atlas space constructed using four-dimensional alignments-for normalized quantitative comparisons. Statistical tests and principal component analyses were conducted on the magnitude of deformations, consonant-specific deformations, and internal muscle strains. The results revealed an overall decrease in deformation intensity following the initial consonant production, indicating potential muscle adaptation behaviors at a later temporal position in one speech utterance.

摘要

识别和量化不同语音环境下软腭发音的语音变化,一直是语音运动控制研究中一个有趣的话题。动态磁共振成像已成为一种有利的工具,用于可视化发音变形,并随着时间推移对语音活动提供定量见解。基于这种模态,有人提出采用一种图像分析技术工作流程,通过改变话语中软腭辅音的位置,来揭示语音环境变化导致的人类舌头潜在变形差异。使用时空跟踪方法从磁共振图像中估计了四名人类受试者在三种不同辅音位置的语音变形,然后通过图像配准将其扭曲到一个公共空间——使用四维对齐构建的动态图谱空间——进行标准化定量比较。对变形幅度、辅音特异性变形和内部肌肉应变进行了统计测试和主成分分析。结果显示,在最初的辅音发音后,变形强度总体下降,表明在一个语音话语的后期时间位置可能存在肌肉适应行为。