Effects of Word Confusion Networks on Voice Search

Proceedings of the 12th Conference of the European Chapter of the ACL, pages 238–245, Athens, Greece, 30 March – 3 April 2009. c⃝2009 Association for Computational Linguistics Effects of Word Confusion Networks on Voice Search Junlan Feng, Srinivas Bangalore AT&T Labs-Research Florham Park, NJ, USA junlan,srini@research.att.com Abstract Mobile voice-enabled search is emerging as one of the most popular applications abetted by the exponential growth in the number of mobile devices. The automatic speech recognition (ASR) output of the voice query is parsed into several fields. Search is then performed on a text corpus or a database. In order to improve the ro- bustness of the query parser to noise in the ASR output, in this paper, we investigate two different methods to query parsing. Both methods exploit multiple hypotheses from ASR, in the form of word confusion networks, in order to achieve tighter cou- pling between ASR and query parsing and improved accuracy of the query parser. We also investigate the results of this improve- ment on search accuracy. Word confusion- network based query parsing outperforms ASR 1-best based query-parsing by 2.7% absolute and the search performance im- proves by 1.8% absolute on one of our data sets. 1 Introduction Local search specializes in serving geographi- cally constrained search queries on a structured database of local business listings. Most text- based local search engines provide two text fields: the “SearchTerm” (e.g. Best Chinese Restau- rant) and the “LocationTerm” (e.g. a city, state, street address, neighborhood etc.). Most voice- enabled local search dialog systems mimic this two-field approach and employ a two-turn dia- log strategy. The dialog system solicits from the user a LocationTerm in the first turn followed by a SearchTerm in the second turn (Wang et al., 2008). Although the two-field interface has been widely accepted, it has several limitations for mo- bile voice search. First, most mobile devices are location-aware which obviates the need to spec- ify the LocationTerm. Second, it’s not always straightforward for users to be aware of the dis- tinction between these two fields. It is com- mon for users to specify location information in the SearchTerm field. For example, “restaurants near Manhattan” for SearchTerm and “NY NY” for LocationTerm. For voice-based search, it is more natural for users to specify queries in a sin- gle utterance1. Finally, many queries often con- tain other constraints (assuming LocationTerm is a constraint) such as that deliver in restaurants that deliver or open 24 hours in night clubs open 24 hours. It would be very cumbersome to enumerate each constraint as a different text field or a dialog turn. An interface that allows for specifying con- straints in a natural language utterance would be most convenient. In this paper, we introduce a voice-based search system that allows users to specify search requests in a single natural language utterance. The out- put of ASR is then parsed by a query parser into three fields: LocationTerm, SearchTerm, and Filler. We use a local search engine, http://www.yellowpages.com/, which accepts the SearchTerm …

Content truncated to 500 words