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With the ubiquity of mobile touchscreen devices like smartphones, two widelyused text entry methods have emerged: small touch-based keyboards and speechrecognition. Although speech recognition has been available on desktopcomputers for years, it has continued to improve at a rapid pace, and it iscurrently unknown how today's modern speech recognizers compare tostate-of-the-art mobile touch keyboards, which also have improved considerablysince their inception. To discover both methods' "upper-bound performance," weevaluated them in English and Mandarin Chinese on an Apple iPhone 6 Plus in alaboratory setting. Our experiment was carried out using Baidu's Deep Speech 2,a deep learning-based speech recognition system, and the built-in Qwerty(English) or Pinyin (Mandarin) Apple iOS keyboards. We found that with speechrecognition, the English input rate was 2.93 times faster (153 vs. 52 WPM), andthe Mandarin Chinese input rate was 2.87 times faster (123 vs. 43 WPM) than thekeyboard for short message transcription under laboratory conditions for bothmethods. Furthermore, although speech made fewer errors during entry (5.30% vs.11.22% corrected error rate), it left slightly more errors in the finaltranscribed text (1.30% vs. 0.79% uncorrected error rate). Our results showthat comparatively, under ideal conditions for both methods, upper-bound speechrecognition performance has greatly improved compared to prior systems, andmight see greater uptake in the future, although further study is required toquantify performance in non-laboratory settings for both methods.

Comparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones