African American English speakers’ pitch variation and rate adjustments for imagined technological and human addressees

Author:

Cohn Michelle12ORCID,Mengesha Zion13,Lahav Michal4,Heldreth Courtney4

Affiliation:

1. Google Research, Google, San Francisco 1 , California 94105, USA

2. Department of Linguistics, University of California 2 , Davis, California 95616, USA

3. Department of Linguistics, Stanford University 3 , Stanford, California 94305, USA

4. Google Research, Google 4 , Seattle, Washington 98103, USA mdcohn@ucdavis.edu , zamengesha@stanford.edu , mlahav@google.com , cheldreth@google.com

Abstract

This paper examines the adaptations African American English speakers make when imagining talking to a voice assistant, compared to a close friend/family member and to a stranger. Results show that speakers slowed their rate and produced less pitch variation in voice-assistant-“directed speech” (DS), relative to human-DS. These adjustments were not mediated by how often participants reported experiencing errors with automatic speech recognition. Overall, this paper addresses a limitation in the types of language varieties explored when examining technology-DS registers and contributes to our understanding of the dynamics of human-computer interaction.

Publisher

Acoustical Society of America (ASA)

Reference55 articles.

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3. Random effects structure for confirmatory hypothesis testing: Keep it maximal;J. Mem. Lang.,2013

4. Bartoń, K. (2017). “ MuMIn: Multi-model inference. R package.,” https://ci.nii.ac.jp/naid/10030918982/ (Last viewed June 2018).

5. Fitting linear mixed-effects models using lme4;J. Stat. Softw.,2015

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