Towards a query language for annotation graphs
Steven Bird, Peter Buneman, Wang-Chiew Tan
Abstract
The multidimensional, heterogeneous, and temporal nature of speech databases raises interesting challenges for representation and query. Recently, annotation graphs have been proposed as a general-purpose representational framework for speech databases. Typical queries on annotation graphs require path expressions similar to those used in semistructured query languages. However, the underlying model is rather different from the customary graph models for semistructured data: the graph is acyclic and unrooted, and both temporal and inclusion relationships are important. We develop a query language and describe optimization techniques for an underlying relational representation.
Create a lesson
Related papers
RSI-Anything: Unlocking Recursive Self-Improvement with World Models
Taoyong Cui, Pinxian Zeng, Wanghan Xu et al.
When VLMs Destroy What They Know: Spatial Representations Fall Below Lexical Priors
Shubh Garg, Chen Shani
Structural Automata for Neural Semantic Parsing
Xiao Zhang
Task Context Shapes Component Roles in Language Models
Sovesh Mohapatra, Dani S Bassett
Can Language Models Learn When to Abstain? Policy Learning and Calibrated Answer Selection
Juan Terven, Diana-Margarita Córdova-Esparza, Ruben Gomez et al.
Error Rate is Not Enough: Costs of Augmentation in Low-Resource ASR
Katsumi Ibaraki, David Chiang