The growing popularity of mobile search and the advancement in voice recognition technologies have opened the door for web search users to speak their queries rather than type them. While this kind of voice search is still in its infancy, it is gradually becoming more widespread. In this article, we report a comprehensive voice search query log analysis of a commercial web search engine's mobile application. We compare voice and text search by various aspects, with special focus on the semantic and syntactic characteristics of the queries. Our analysis suggests that voice queries focus more on audio-visual content and question answering and less on social networking and adult domains. In addition, voice queries are more commonly submitted on the go. We also conduct an empirical evaluation showing that the language of voice queries is closer to natural language than the language of text queries. Our analysis points out further differences between voice and text search. We discuss the implications of these differences for the design of future voice-enabled web search tools.
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