Voice interfaces to browsers and mobile applications are becoming popular as typing with touch screens is cumbersome. The main issue of practical speech based interfaces is how to overcome speech recognition errors. This problem is more severe when the users are non-native speakers of English due to differences in pronunciations. In this paper, we describe a novel, intelligent speech interface design approach for IR tasks that is significantly robust to accent variations. Our solution uses phonemic similarity based word spreading and semantic information based filtering to boost the accuracy of any ASR. We evaluated our solution with Google Voice as the ASR for a web question-answering system developed in-house and the results are very encouraging. Copyright is held by the author/owner(s).