{"title":"Head correction of point tracking data","authors":"Keith A. Johnson, Ronald L. Sprouse","doi":"10.5070/p7151050341","DOIUrl":null,"url":null,"abstract":"Author(s): Johnson, Keith; Sprouse, Ronald L. | Abstract: This is a short paper comparing two approaches to head correction for Electro-MagneticArticulography (EMA) data collected with the Northern Digital Instruments “Wave” system. Inboth of these approaches, it is necessary to translate and rotate the sensor locations to theocclusal coordinate system. We found that point tracking error is greater by as much as doublewith the built-in NDI head correction method, compared to a three-sensor head correctionalgorithm. However, we conclude that the data are comparable, and that the two-sensor NDImethod is acceptable for phonetic research. A Python library for head correction was developedfor this work, and is available on github.com.","PeriodicalId":440264,"journal":{"name":"UC Berkeley Phonology Lab Annual Reports","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"UC Berkeley Phonology Lab Annual Reports","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5070/p7151050341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Author(s): Johnson, Keith; Sprouse, Ronald L. | Abstract: This is a short paper comparing two approaches to head correction for Electro-MagneticArticulography (EMA) data collected with the Northern Digital Instruments “Wave” system. Inboth of these approaches, it is necessary to translate and rotate the sensor locations to theocclusal coordinate system. We found that point tracking error is greater by as much as doublewith the built-in NDI head correction method, compared to a three-sensor head correctionalgorithm. However, we conclude that the data are comparable, and that the two-sensor NDImethod is acceptable for phonetic research. A Python library for head correction was developedfor this work, and is available on github.com.
作者:约翰逊,基思;摘要:这是一篇比较两种方法对由美国北方数字仪器公司(Northern Digital Instruments)“Wave”系统收集的电磁关节成像(EMA)数据进行头部校正的短文。在这两种方法中,都需要将传感器位置平移和旋转到咬合坐标系。我们发现,与三传感器头校正算法相比,内置NDI头校正方法的点跟踪误差更大,高达两倍。然而,我们得出的结论是,数据具有可比性,并且双传感器ndi方法可用于语音研究。为这项工作开发了一个用于头部校正的Python库,可以在github.com上获得。