Title :
A grammar compiler for connected speech recognition
Author :
Brown, Michael K. ; Wilpon, Jay G.
Author_Institution :
AT&T Bell Lab., Murray Hill, NJ, USA
fDate :
1/1/1991 12:00:00 AM
Abstract :
A compiler for constructing optimized syntactic digraphs from easily written grammar specifications is described. These are written in a language called grammar specification language (GSL). The compiler has a preprocessing (macroexpansion) phase, a parse phase, graph code generation and compilation phases, and three optimization phases. Digraphs can also be linked together by a graph linker to form larger digraphs. Language complexity is analyzed in a statistics phase. It is demonstrated that the optimization phase yields graphs with even greater efficiency than previously achieved by hand. Some preliminary speech recognition results of applying these techniques to intermediate and large graphs are discussed. With the introduction of these tools it is now possible to provide a speech recognition user with the ability to define new task grammars in the field. GSL has been used by several untutored users with good results. Experience with GSL indicates that it is a viable medium for quickly and accurately defining grammars for use in connected speech recognition systems
Keywords :
directed graphs; grammars; program compilers; specification languages; speech recognition; compilation phases; connected speech recognition; grammar compiler; grammar specification language; graph code generation; optimization phases; optimized syntactic digraphs; parse phase; preprocessing phase; statistics phase; Automata; Automatic control; Automatic speech recognition; Intelligent robots; Optimizing compilers; Robot control; Specification languages; Speech recognition; Statistical analysis; Vocabulary;
Journal_Title :
Signal Processing, IEEE Transactions on