Speech-Based Text Correction Patterns in Noisy Environment

Abstract

We present a study focused on observation of methods of dictation and error correction between humans in a noisy environment. The purpose of this study is to gain insight to natural communication patterns which can then be applied to human -machine interaction. We asked 10 subjects to conduct the standard Lane Change Test (LCT) while dictating messages to a human counterpart who had to note down the message texts. Both parties were located in separate rooms and communicated over Skype. Both were exposed to varying types and levels of noise, which made their communication difficult and forced the subjects to deal with misunderstandings. Dictation of both short and longer messages was tested. We observed how the subjects behaved and we analyzed their communication patterns. We identified and described more then 20 elementary observations related to communication techniques such as synchronization and grounding of parties, error checking and error correction. We also report frequencies of use for each communication pattern and provide basic characteristics of driving distraction during the test.