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Language bias, both positive and negative, is a well-documented phenomenon exhibited among human interlocutors. We examine whether this bias is exhibited toward virtual assistants, specifically, Apple's Siri and Google Assistant, with various accents. We conducted three studies with different stimuli and designs to investigate U.S. English speakers’ attitudes toward Google's British, Indian, and American voices and Apple's Irish, Indian, South African, British, Australian, and American voices. Analysis reveals consistently lower fluency ratings for Irish, Indian, and South African voices (compared with American) but no consistent results of bias related to competence, warmth, or willingness to interact. Moreover, participants often misidentified voices’ countries of origin but correctly identified them as artificial. We conclude that this overall lack of bias may be due to two possibilities: lack of humanlikeness of the voices and lack of availability of nonstandardized voices and voices from countries toward which those in the United States typically show bias.
Language bias, both positive and negative, is a well-documented phenomenon exhibited among human interlocutors. We examine whether this bias is exhibited toward virtual assistants, specifically, Apple's Siri and Google Assistant, with various accents. We conducted three studies with different stimuli and designs to investigate U.S. English speakers’ attitudes toward Google's British, Indian, and American voices and Apple's Irish, Indian, South African, British, Australian, and American voices. Analysis reveals consistently lower fluency ratings for Irish, Indian, and South African voices (compared with American) but no consistent results of bias related to competence, warmth, or willingness to interact. Moreover, participants often misidentified voices’ countries of origin but correctly identified them as artificial. We conclude that this overall lack of bias may be due to two possibilities: lack of humanlikeness of the voices and lack of availability of nonstandardized voices and voices from countries toward which those in the United States typically show bias.
The verbal guise test (VGT) is considered a modified iteration of the classical matched guise test. Over the years, the VGT has found application in a spectrum of studies concerning language attitudes toward different accents and varieties. Despite its widespread use in language attitude research, the VGT is not without inherent challenges, such as the quality of audio clips and participant sampling techniques. These limitations have been acknowledged by researchers as commonplace, but thorough discussions and practical solutions to address these limitations have been relatively scarce, with Chan being a notable exception. This chapter endeavors to offer valuable recommendations to researchers who employ the VGT in their studies by examining recent research endeavors that have incorporated the verbal guise test and by providing a comprehensive overview of the test's historical evolution. The chapter aims to reintroduce this classical tool to contemporary language attitude researchers while engaging in a modern discourse about effective approaches to mitigate its limitations.
The verbal guise test, also known as the verbal guise technique, comprises a longstanding history in linguistic research, particularly within the realms of language attitudes and language variations. This method is considered a modified iteration of the classical matched guise test (or matched guise technique). Over the years, the verbal guise test has found application in a spectrum of studies concerning language attitudes toward different accents and varieties, encompassing both inner circle Englishes and outer circle Englishes. Despite its widespread use in language attitude research, the verbal guise test is not without inherent challenges, such as the quality of audio clips and participant sampling techniques. These limitations have been acknowledged by researchers as commonplace, but thorough discussions and practical solutions to address these limitations have been relatively scarce, with Chan being a notable exception. This chapter endeavors to offer valuable recommendations to researchers who employ the verbal guise technique in their studies by examining recent research endeavors that have incorporated the verbal guise test and by providing a comprehensive overview of the test's historical evolution. The chapter aims to reintroduce this classical tool to contemporary language attitude researchers while engaging in a modern discourse about effective approaches to mitigate its limitations.
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