Purpose: Delayed auditory feedback (DAF) interferes with speech output. DAF causes distorted and disfluent productions and errors in the serial order of produced sounds. Although DAF has been studied extensively, the specific patterns of elicited speech errors are somewhat obscured by relatively small speech samples, differences across studies, and uncontrolled variables. The goal of this study was to characterize the types of serial order errors that increase under DAF in a systematic syllable sequence production task, which used a closed set of sounds and controlled for speech rate. Method: Sixteen adult speakers repeatedly produced CVCVCV (C = consonant, V = vowel) sequences, paced to a “visual metronome,” while hearing self-generated feedback with delays of 0–250 ms. Listeners transcribed recordings, and speech errors were classified based on the literature surrounding naturally occurring slips of the tongue. A series of mixed-effects models were used to assess the effects of delay for different error types, for error arrival time, and for speaking rate. Results: DAF had a significant effect on the overall error rate for delays of 100 ms or greater. Statistical models revealed significant effects (relative to zero delay) for vowel and syllable repetitions, vowel exchanges, vowel omissions, onset disfluencies, and distortions. Serial order errors were especially dominated by vowel and syllable repetitions. Errors occurred earlier on average within a trial for longer feedback delays. Although longer delays caused slower speech, this effect was mediated by the run number (time in the experiment) and small compared with those in previous studies. Conclusions: DAF drives a specific pattern of serial order errors. The dominant pattern of vowel and syllable repetition errors suggests possible mechanisms whereby DAF drives changes to the activity in speech planning representations, yielding errors. These mechanisms are outlined with reference to the GODIVA (Gradient Order Directions Into Velocities of Articulators) model of speech planning and production. Supplemental Material: https://doi.org/10.23641/asha.19601785
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Speech Rate Adjustments in Conversations With an Amazon Alexa Socialbot
This paper investigates users’ speech rate adjustments during conversations with an Amazon Alexa socialbot in response to situational (in-lab vs. at-home) and communicative (ASR comprehension errors) factors. We collected user interaction studies and measured speech rate at each turn in the conversation and in baseline productions (collected prior to the interaction). Overall, we find that users slow their speech rate when talking to the bot, relative to their pre-interaction productions, consistent with hyperarticulation. Speakers use an even slower speech rate in the in-lab setting (relative to at-home). We also see evidence for turn-level entrainment: the user follows the directionality of Alexa’s changes in rate in the immediately preceding turn. Yet, we do not see differences in hyperarticulation or entrainment in response to ASR errors, or on the basis of user ratings of the interaction. Overall, this work has implications for human-computer interaction and theories of linguistic adaptation and entrainment.
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- Award ID(s):
- 1911855
- NSF-PAR ID:
- 10275334
- Date Published:
- Journal Name:
- Frontiers in Communication
- Volume:
- 6
- ISSN:
- 2297-900X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fcomm.2021.671429
