Abstract
This work provides a descriptive analysis of the tone direction and its inherent illocutionary force in question tags delivered by Amazon’s neural text-to-speech system Polly. We included three types of tag questions (reverse-polarity tags — both positive and negative —, copy tags and command tags) for which 10 sentences were used as input in each case. The data included 600 utterances produced by British and American English voices currently available on Amazon’s NTTS. The audio files were examined with the speech analysis software Praat to identify the tone pattern for each utterance and confirm the intended illocutionary force. The results show that Amazon’s AI speech synthesis technology is not yet fully reliable and produces a high rate of utterances whose pragmatic load is undesired when using natural spontaneous speech traits as question tags.
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