What Do Viewers Say to Their TVs?
Author:
Affiliation:
1. University of Maryland & Comcast Applied AI Research Lab, College Park, MD, USA
2. Comcast Applied AI Research Lab, Washington, DC, USA
3. University of Waterloo, Waterloo, ON, Canada
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3209978.3210140
Reference12 articles.
1. A. Acero N. Bernstein R. Chambers Y. C. Ju X. Li J. Odell P. Nguyen O. Scholz and G. Zweig. 2008. Live Search for Mobile: Web Services by Voice on the Cellphone. ICASSP. A. Acero N. Bernstein R. Chambers Y. C. Ju X. Li J. Odell P. Nguyen O. Scholz and G. Zweig. 2008. Live Search for Mobile: Web Services by Voice on the Cellphone. ICASSP.
2. C. Chelba and J. Schalkwyk. 2013. Empirical Exploration of Language Modeling for the google.com Query Stream as Applied to Mobile Voice Search. Mobile Speech and Advanced Natural Language Solutions. C. Chelba and J. Schalkwyk. 2013. Empirical Exploration of Language Modeling for the google.com Query Stream as Applied to Mobile Voice Search. Mobile Speech and Advanced Natural Language Solutions.
3. J. Feng and S. Bangalore. 2009. Effects of Word Confusion Networks on Voice Search. EACL. J. Feng and S. Bangalore. 2009. Effects of Word Confusion Networks on Voice Search. EACL.
4. I. Guy. 2016. Searching by Talking: Analysis of Voice Queries on Mobile Web Search. SIGIR. 10.1145/2911451.2911525 I. Guy. 2016. Searching by Talking: Analysis of Voice Queries on Mobile Web Search. SIGIR. 10.1145/2911451.2911525
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2. Challenges and Opportunities in Understanding Spoken Queries Directed at Modern Entertainment Platforms;Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval;2019-07-18
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