Doctoral Dissertation Research: Interviewer Voice Characteristics and Data Quality

电话采访经常包含社会希望的、社会不希望的和复杂的问题，这些问题往往会给受访者带来问题。对于这类问题，说话者特别有可能改变发音方式。这些变化可能直接影响数据质量，也可能通过听者对语音的感知间接影响数据质量。由于电话调查仍然是许多大型国家研究的主要数据收集模式，因此了解采访者的声音如何影响数据质量是很重要的。这项研究将考察面试者的声音特征是否会影响社会期望的、不期望的和复杂的调查问题的数据质量。在电话采访中，面试者的声音是与受访者沟通的主要方式。如果面试者的语音特征影响数据质量，那么负责面谈的人员可以选择或培训面试者来修改他们的某些语音特征，以达到最大限度地提高数据质量的目标。此外，这项研究的结果将有助于根据语音特征为音频计算机辅助自访(ACASI)、电话音频-CASI(T-ACASI)和交互式语音应答(IVR)系统选择面试者，目标是将测量误差降至最低。作为博士论文研究改进奖，提供支持使有前途的学生建立一个强大的，独立的研究事业。该项目将评估电话调查访问者的客观声音特征(包括语速、音调、语调和不流利性)是否与听者对这些声音特征的主观感知以及他们对访问者的五个主观特征(可信度、自信、可靠性、可信度和易懂)的评估有关。该项目还将研究电话调查访问者的客观声音特征是否会影响社会合意、社会不合意和复杂问题的数据质量。最后，该项目将调查面试官对语音的主观感知是否在客观语音特征和数据质量之间的关系中起到中介作用。这项研究将使用Praat计算机软件程序客观地测量面试者的声音特征，并使用评分器在七分制上主观地评估声音特征(例如音调和语速)和面试者特征(例如可信度和信心)。分层Logistic回归模型将被用来检验客观和主观语音特征与数据质量之间的关联。数据质量的衡量标准包括所有问题的项目无反应，复杂和中性问题的四舍五入答案(例如5，10)，以及更多/更少的方向性假设更适合于社会不希望/希望的问题。

Telephone interviews frequently contain socially desirable, socially undesirable, and complex questions that tend to produce problems for respondents. A speaker may be especially likely to change vocal patterns for these types of questions. These changes may either directly affect data quality or indirectly affect data quality through the listener's perception of the voice. As telephone surveys continue to be the primary mode of data collection for many large national studies, it is important to understand how interviewer voices affect data quality. This study will examine whether interviewer voice characteristics affect data quality in socially desirable, undesirable, and complex survey questions. Interviewer voices are the primary means of communication to respondents in telephone interviews. If voice characteristics of interviewers affect data quality, those overseeing interviews may be able to select or train interviewers to modify some of their vocal characteristics with the goal of maximizing data quality. Moreover, results from this research will be useful for selecting interviewers based on voice characteristics for audio computer-assisted self-interviewing (ACASI), telephone audio-CASI (T-ACASI), and interactive voice response (IVR) systems with the goal of minimizing measurement error. As a Doctoral Dissertation Research Improvement award, support is provided to enable a promising student to establish a strong, independent research career.Specifically, this study has three objectives. The project will evaluate whether a telephone survey interviewer's objective voice characteristics including speech rate, pitch, intonation, and disfluency are associated with a listener's subjective perception of these voice characteristics and their assessment of five subjective interviewer traits (credibility, confidence, reliability, trustworthiness, and easiness to understand). The project also will examine whether objective voice characteristics of telephone survey interviewers affect data quality in socially desirable, socially undesirable, and complex questions. Finally, the project will investigate whether subjective perceptions of an interviewer's voice mediate the relationship between objective voice characteristics and data quality. The study will objectively measure interviewer's voice characteristics by using the Praat computer software program and will use raters to subjectively evaluate voice characteristics (e.g. pitch and speaking rate) and interviewer traits (e.g. credibility, confidence) on seven-point scales. Hierarchical logistic regression models will be used to examine the association between the objective and subjective voice characteristics and data quality. Measures of data quality include item nonresponse for all questions, rounding answers (e.g. 5, 10) for complex and neutral questions, and the directional hypothesis of more/less is better for socially undesirable/desirable questions.