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- W4384694578 abstract "Voice assistants are a subset of speech recognition technology that continue to exponentially improve in terms of their accessibility and functionality in response to user voice commands. The current research examined the effects of speaker accent, speech quality, and speech rate on syntactic and semantic interpretation accuracy for the voice assistant Siri. 60 adult participants read standardized command phrases to Siri to determine syntactic and semantic interpretation accuracy differences between Canadian and non-Canadian accents, masked and unmasked speaking, and slow, moderate, and fast rates of speech. Analyses demonstrated that poorer speech quality inputs resulted in significantly lower syntactic and semantic accuracy interpretation scores. Furthermore, non-Canadian accents generated significantly lower semantic accuracy interpretation scores. Accuracy measurements for speech rate and speaker accent (syntactic accuracy) did not support previous research findings. These results signify the importance of additional algorithmic training improvements and continuing to investigate influential factors on voice assistant response accuracy." @default.
- W4384694578 created "2023-07-20" @default.
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- W4384694578 date "2023-07-18" @default.
- W4384694578 modified "2023-09-25" @default.
- W4384694578 title "Talking With Siri: Analyzing and Detecting Error Patterns in Speech Recognition Technology" @default.
- W4384694578 doi "https://doi.org/10.22215/etd/2023-15473" @default.
- W4384694578 hasPublicationYear "2023" @default.
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