With the ubiquity of mobile devices like smartphones, two new widely used methods have emerged: miniature touch screen keyboards and speech-based dictation. It is currently unknown how these two modern methods compare. We therefore evaluated the text entry performance of both methods in English and in Mandarin Chinese on a mobile smartphone. In the speech input case, our speech recognition system gave an initial transcription, and then recognition errors could be corrected using either speech again or the smartphone keyboard.

We found that with speech recognition, the English input rate was 3.0x faster, and the Mandarin Chinese input rate 2.8x faster, than a state-of-the-art miniature smartphone keyboard. Further, with speech, the English error rate was 20.4% lower, and Mandarin error rate 63.4% lower, than the keyboard. Our experiment was carried out using Baidu’s Deep Speech 2, a deep learning-based speech recognition system, and the built-in Qwerty or Pinyin (Mandarin) Apple iOS keyboards. These results show that a significant shift from typing to speech might be imminent and impactful. Further research to develop effective speech interfaces is warranted.

This study was conducted by researchers from Stanford University, University of Washington, and Baidu.

Source: Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices

Categories: Uncategorized

Related Posts

Uncategorized

Becoming a 10x Data Scientist – Algorithmia

Borrowing tips and tricks from software developers, learn how to create a more productive workflow on the journey to becoming a 10X Data Scientist. Source: Becoming a 10x Data Scientist – Algorithmia Related PostsTrey Causey Read more…

Uncategorized

Announcing Rust 1.20 – The Rust Programming Language Blog

curl https://sh.rustup.rs -sSf | sh rustup update stable Source: Announcing Rust 1.20 – The Rust Programming Language Blog Related PostsIn Defense of C++Principles for C programming – Drew DeVault’s BlogVulnerability announced: update your Git clientsVulnerability Read more…

Uncategorized

Documentation and Analysis of the Linux Random Number Generator – LinuxRNG_EN.pdf

Source: Documentation and Analysis of the Linux Random Number Generator – LinuxRNG_EN.pdf Related Postsscikit-bio — scikit-bio 0.2.3 documentationComputational Statistics in Python — Computational Statistics in Python 0.1 documentationWhat’s New In Python 3.5 — Python 3.5.0b2 Read more…