Searching by Talking

TLDR

Mobile search and voice‑recognition advances have enabled users to speak queries, and voice search is becoming increasingly common. The study examines logs from a commercial mobile search engine to compare spoken and typed queries. The authors analyze semantic and syntactic features of spoken versus typed queries and empirically evaluate their natural‑language similarity. Voice queries emphasize audio‑visual content and question answering, are closer to natural language, and differ from typed queries, informing future voice‑search design.

Abstract

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 paper, we examine the logs of a commercial search engine's mobile interface, and compare the spoken queries to the typed-in queries. We place special emphasis on the semantic and syntactic characteristics of the two types of queries. %Our analysis suggests that voice queries focus more on audio-visual content and question answering, and less on social networking and adult domains. We also conduct an empirical evaluation showing that the language of voice queries is closer to natural language than typed queries. Our analysis reveals further differences between voice and text search, which have implications for the design of future voice-enabled search tools.