Voice Query Auto Completion

Query auto completion (QAC) is the task of predicting a search engine user's final query from their intermediate, incomplete query. In this paper, we extend QAC to the streaming voice search setting, where automatic speech recognition systems produce intermediate transcripts as users speak. Naïvely applying existing methods fails because the intermediate transcripts often don't form prefixes or even substrings of the final transcript. To address this issue, we propose to condition QAC approaches on intermediate transcripts to complete voice queries. We evaluate our models on a speech-enabled smart television with reallife voice search traffic, finding that this ASRaware conditioning improves the completion quality. Our best method obtains an 18% relative improvement in mean reciprocal rank over previous methods.