Paper Info
Title
Rapid Vocabulary Addition To Context-Dependent Decoder Graphs
Abstract
We describe how to efficiently add new vocabulary directly to an existing optimized ASR decoder graph. The augmented decoder graph is represented by two weighted finite-state transducers, a primary graph that represents the static portion and a secondary graph that represents the dynamic portion, together with a mapping that specifies that some states in the two graphs are to be merged. Determinism is obtained by excluding from the secondary graph any prefixes already present in the primary graph. Correct context-dependency is obtained by including in the primary graph all prefixes needed to properly merge with the secondary graph. We report experiments comparing this approach to an existing one that requires on-the-fly construction of the decoder graph.
Year
Venue
Keywords
2015
16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5
speech recognition, decoding architecture, finite state transducers
Field
DocType
Citations 
Graph,Computer science,Speech recognition,Artificial intelligence,Natural language processing,Vocabulary
Conference
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Cyril Allauzen169047.64
Michael Riley21697243.58