Database Paper Browser

Back to papers

Robust Voice Querying with MUVE: Optimally Visualizing Results of Phonetically Similar Queries

Summary: MUVE visualizes phonetically similar voice-to-SQL results as multiplots to curb ASR ambiguity. It maps voice input to a candidate distribution, selects a subset of queries, and optimizes visualization to minimize the expected time to identify the correct result; NP-hard, with IP-based exact and greedy solvers, validated by a user study. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12415
Venue
VLDB
Year
2021
Pagerank
4.1945683e-05
Overall Rank
11,506 | 19.96%
DOI
10.14778/3476249.3476289

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers