Doctoral Dissertation Research: Interviewer Voice Characteristics and Data Quality

电话访谈通常包含社会期望的、社会不期望的和复杂的问题，这些问题往往会给应答者带来麻烦。对于这些类型的问题，说话者可能特别有可能改变声音模式。这些变化可能直接影响数据质量，也可能通过听者对声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数据收集的主要模式，因此了解采访者的声音如何影响数据质量非常重要。本研究将检验采访者的声音特征是否会影响社会期望、不期望和复杂调查问题的数据质量。在电话访谈中，访谈者的声音是与应答者沟通的主要方式。如果采访者的声音特征影响数据质量，那些监督访谈的人可能能够选择或培训采访者修改他们的一些声音特征，以最大限度地提高数据质量。此外，本研究的结果将有助于在音频计算机辅助自我访谈（ACASI）、电话音频- casi （T-ACASI）和交互式语音应答（IVR）系统中选择基于语音特征的采访者，以最大限度地减少测量误差。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，独立的研究生涯。具体来说，本研究有三个目标。该项目将评估电话调查采访者的客观声音特征（包括语速、音高、语调和不流畅度）是否与听者对这些声音特征的主观感知以及他们对采访者五种主观特征（可信度、信心、可靠性、可信赖性和易于理解）的评估有关。该项目还将研究电话调查采访者的客观声音特征是否会影响社会期望、社会不期望和复杂问题的数据质量。最后，该项目将调查采访者声音的主观感知是否介导客观声音特征和数据质量之间的关系。该研究将使用Praat计算机软件程序客观地测量采访者的声音特征，并将使用评分者主观地评估声音特征（如音高和语速）和采访者特征（如可信度，信心），分为七分制。层次逻辑回归模型将用于检查客观和主观语音特征和数据质量之间的关联。数据质量的测量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/更少的定向假设对于社会不希望/理想的问题更好。

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.