System and method for tying variance vectors for speech recognition
AssigneesSony Corporation, Sony Electronics Inc.
InventorsXavier Menendez-Pidal, Ajay Patrikar
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Abstract
A system and method for implementing a speech recognition engine includes acoustic models that the speech recognition engine utilizes to perform speech recognition procedures. An acoustic model optimizer performs a vector quantization procedure upon original variance vectors initially associated with the acoustic models. In certain embodiments, the vector quantization procedure may be performed as a block vector quantization procedure or as a subgroup vector quantization procedure. The vector quantization procedure produces a reduced number of tied variance vectors for optimally implementing the acoustic models.
Claims41
A system for implementing a speech recognition engine, comprising:
- acoustic models that said speech recognition engine utilizes to perform speech recognition procedures;
- and
- an acoustic model optimizer that performs a vector quantization procedure upon original variance vectors initially associated with said acoustic models, said vector quantization procedure producing a number of compressed variance vectors less than the number of said original variance vectors, said compressed variance vectors then being used in said acoustic models in place of said original variance vectors.
A method for implementing a speech recognition engine, comprising:
- defining acoustic models for performing speech recognition procedures;
- and
- utilizing an acoustic model optimizer to perform a vector quantization procedure upon original variance vectors initially associated with said acoustic models, said vector quantization procedure producing a number of compressed variance vectors less than the number of said original variance vectors, said compressed variance vectors then being used in said acoustic models in place of said original variance vectors.
A system for implementing a speech recognition engine, comprising:
- means for defining acoustic models to perform speech recognition procedures;
- and
- means for performing a vector quantization procedure upon original variance vectors initially associated with said acoustic models, said vector quantization procedure producing a number of compressed variance vectors less than the number of said original variance vectors, said compressed variance vectors then being used in said acoustic models in place of said original variance vectors.
Dependencies are inferred from the claim text.