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.
- A. Acero, N. Bernstein, R. Chambers, Y. Ju, X. Li, J. Odell, P. Nguyen, O. Scholz, and G. Zweig. Live search for mobile: Web services by voice on the cellphone. In Proc. ICASSP, pages 5256--5259, 2008.Google Scholar
- L. A. Adamic, J. Zhang, E. Bakshy, and M. S. Ackerman. Knowledge sharing and yahoo answers: Everyone knows something. In Proc. WWW, pages 665--674, 2008. Google ScholarDigital Library
- A. H. Awadallah, R. Gurunath Kulkarni, U. Ozertem, and R. Jones. Characterizing and predicting voice query reformulation. In Proc. CIKM, pages 543--552, 2015. Google ScholarDigital Library
- R. Baeza-Yates, G. Dupret, and J. Velasco. A study of mobile search queries in japan. In Query Log Analysis (WWW workshop), 2007.Google Scholar
- C. Barr, R. Jones, and M. Regelson. The linguistic structure of english web-search queries. In Proc. EMNLP, pages 1021--1030, 2008. Google ScholarDigital Library
- A. Berger and J. Lafferty. Information retrieval as statistical translation. In Proc. SIGIR, pages 222--229, 1999. Google ScholarDigital Library
- B. L. Chalfonte, R. S. Fish, and R. E. Kraut. Expressive richness: A comparison of speech and text as media for revision. In Proc. CHI, pages 21--26, 1991. Google ScholarDigital Library
- C. Chelba and J. Schalkwyk. Empirical exploration of language modeling for the google.com query stream as applied to mobile voice search. In Mobile Speech and Advanced Natural Language Solutions, pages 197--229. 2013.Google ScholarCross Ref
- L. B. Chilton and J. Teevan. Addressing people's information needs directly in a web search result page. In Proc. WWW, pages 27--36, 2011. Google ScholarDigital Library
- F. Crestani and H. Du. Written versus spoken queries: A qualitative and quantitative comparative analysis. JASIST, 57(7):881--890, 2006. Google ScholarDigital Library
- M.-C. De Marneffe, B. MacCartney, and C. D. Manning. Generating typed dependency parses from phrase structure parses. In Proc. LREC, pages 449--454, 2006.Google Scholar
- G. Dror, Y. Maarek, A. Mejer, and I. Szpektor. From query to question in one click: Suggesting synthetic questions to searchers. In Proc. WWW, pages 391--402, 2013. Google ScholarDigital Library
- A. Easwara Moorthy and K.-P. L. Vu. Privacy concerns for use of voice activated personal assistant in the public space. International Journal of Human-Computer Interaction, 31(4):307--335, 2015.Google ScholarCross Ref
- Google official blog. http://googleblog.blogspot.co.il/2014/10/omg-mobile-voice-survey-reveals-teens.html. {Accessed 2016-05-01}.Google Scholar
- M. Gupta and M. Bendersky. Information retrieval with verbose queries. Foundations and Trends in Information Retrieval, 9(3-4):209--354, 2015.Google ScholarCross Ref
- I. Guy and D. Pelleg. The factoid queries collection. In PROC. SIGIR, 2016. Google ScholarDigital Library
- G. Hinton, L. Deng, D. Yu, G. Dahl, A. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. Sainath, and B. Kingsbury. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. Signal Processing Magazine, 29(6):82--97, 2012.Google ScholarCross Ref
- J. Jiang, A. Hassan Awadallah, R. Jones, U. Ozertem, I. Zitouni, R. Gurunath Kulkarni, and O. Z. Khan. Automatic online evaluation of intelligent assistants. In Proc. WWW, pages 506--516, 2015. Google ScholarDigital Library
- J. Jiang, W. Jeng, and D. He. How do users respond to voice input errors? lexical and phonetic query reformulation in voice search. In Proc. SIGIR, pages 143--152, 2013. Google ScholarDigital Library
- M. Kamvar and S. Baluja. A large scale study of wireless search behavior: Google mobile search. In CHI, pages 701--709, 2006. Google ScholarDigital Library
- M. Kamvar, M. Kellar, R. Patel, and Y. Xu. Computers and iphones and mobile phones, oh my!: A logs-based comparison of search users on different devices. In Proc. WWW, pages 801--810, 2009. Google ScholarDigital Library
- D. Klein and C. D. Manning. Accurate unlexicalized parsing. In Proc. ACL, pages 423--430, 2003. Google ScholarDigital Library
- D. Lagun, C.-H. Hsieh, D. Webster, and V. Navalpakkam. Towards better measurement of attention and satisfaction in mobile search. In Proc. SIGIR, pages 113--122, 2014. Google ScholarDigital Library
- J. Li, S. Huffman, and A. Tokuda. Good abandonment in mobile and pc internet search. In PROC. SIGIR, pages 43--50, 2009. Google ScholarDigital Library
- C. Y. Lin. Automatic question generation from queries. In Workshop on the Question Generation Shared Task, pages 156--164, 2008.Google Scholar
- M. P. Marcus, M. A. Marcinkiewicz, and B. Santorini. Building a large annotated corpus of english: The penn treebank. Computational linguistics, 1993. Google ScholarDigital Library
- A. Moreno-Daniel, S. Parthasarathy, B. Juang, and J. Wilpon. Spoken query processing for information retrieval. In Proc. ICASSP, volume 4, pages IV--121--IV--124, 2007.Google Scholar
- Y. Pinter, R. Reichart, and I. Szpektor. Syntactic parsing of web queries with question intent: A distant supervision approach, 2016. Proc. NAACL.Google ScholarCross Ref
- R. Rosenfield. Two decades of statistical language modeling: Where do we go from here? Proceedings of the IEEE, 2000.Google ScholarCross Ref
- J. Schalkwyk, D. Beeferman, F. Beaufays, B. Byrne, C. Chelba, M. Cohen, M. Kamvar, and B. Strope. Your word is my command: Google search by voice: A case study. In Advances in Speech Recognition, pages 61--90. 2010.Google ScholarCross Ref
- J. Shan, G. Wu, Z. Hu, X. Tang, M. Jansche, and P. J. Moreno. Search by voice in mandarin chinese. In Proc. INTERSPEECH, pages 354--357, 2010.Google ScholarCross Ref
- M. Shokouhi and Q. Guo. From queries to cards: Re-ranking proactive card recommendations based on reactive search history. In Proc. SIGIR, pages 695--704, 2015. Google ScholarDigital Library
- M. Shokouhi, R. Jones, U. Ozertem, K. Raghunathan, and F. Diaz. Mobile query reformulations. In Proc. SIGIR, pages 1011--1014, 2014. Google ScholarDigital Library
- Y. Song, H. Ma, H. Wang, and K. Wang. Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance. In Proc. WWW, pages 1201--1212, 2013. Google ScholarDigital Library
- J. Teevan, D. Ramage, and M. R. Morris.#twittersearch: A comparison of microblog search and web search. In Proc. WSDM, pages 35--44, 2011. Google ScholarDigital Library
- K. Toutanova, D. Klein, C. D. Manning, and Y. Singer. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proc. NAACL, pages 173--180, 2003. Google ScholarDigital Library
- S. Verberne. Paragraph retrieval for why-question answering. In Proc. SIGIR, pages 922--922, 2007. Google ScholarDigital Library
- Y. Y. Wang, D. Yu, Y.-C. Ju, and A. Acero. An introduction to voice search. Signal Processing Magazine, 25(3):28--38, 2008.Google ScholarCross Ref
- R. W. White, M. Richardson, and W. Yih. Questions vs. queries in informational search tasks. In Proc. WWW, pages 135--136, 2015. Google ScholarDigital Library
- J. Yi and F. Maghoul. Mobile search pattern evolution: The trend and the impact of voice queries. In Proc. WWW, pages 165--166, 2011. Google ScholarDigital Library
- J. Yi, F. Maghoul, and J. Pedersen. Deciphering mobile search patterns: A study of yahoo! mobile search queries. In Proc. WWW, pages 257--266, 2008. Google ScholarDigital Library
- C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Proc. SIGIR, pages 334--342, 2001. Google ScholarDigital Library
- G. Zweig and S. Chang. Personalizing model m for voice-search. In Proc. INTERSPEECH, pages 609--612, 2011.Google ScholarCross Ref
Index Terms
- Searching by Talking: Analysis of Voice Queries on Mobile Web Search
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