Speech recognition error diagnosis

The system of claim 0, wherein the recognition error diagnostics module is configured to:

• determine that the at least one category of recognition error includes at least an acoustic model error and a language model error when
• (a) the first error analysis result indicates that a reference language model score associated with a reference speech is lower than a recognition language model score associated with the at least partially erroneous speech recognition result;
• and
• (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is lower than a recognition acoustic model score associated with the at least partially erroneous speech recognition result.

The system of claim 0, wherein the recognition error diagnostics module is configured to:

• determine that the at least one category of recognition error includes at least an acoustic model error when
• (a) the first error analysis result indicates that a reference language model score associated with a reference speech is higher than a recognition language model score associated with the at least partially erroneous speech recognition result;
• and
• (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is lower than a recognition acoustic model score associated with the at least partially erroneous speech recognition result.

The system of claim 0, wherein the recognition error diagnostics module is configured to:

• determine that the at least one category of recognition error includes at least an language model error and a pruning model error when
• (a) the first error analysis result indicates that a reference language model score associated with a reference speech is lower than a recognition language model score associated with the at least partially erroneous speech recognition result;
• and
• (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is higher than a recognition acoustic model score associated with the at least partially erroneous speech recognition result.

The system of claim 0, wherein the recognition error diagnostics module is configured to:

• determine that the at least one category of recognition error includes at least a penalty model error when
• (a) the first error analysis result indicates that a reference language model score associated with a reference speech is higher than a recognition language model score associated with the at least partially erroneous speech recognition result;
• and
• (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is higher than a recognition acoustic model score associated with the at least partially erroneous speech recognition result.

An apparatus for diagnosing speech recognition errors, comprising:

• at least one processing component;
• and
• one or more computer-readable media operably coupled to the at least one processing component and bearing one or more instructions that, when executed by the at least one processing component, perform operations including at least:
• performing one or more speech recognition operations to provide a speech recognition result;
• performing a first error analysis of the speech recognition result to provide a first error analysis result;
• performing a second error analysis of the speech recognition result to provide a second error analysis result;
• and
• determining at least one corrective action to at least partially increase an operability of at least one of the one or more speech recognition operations based on a combination of at least the first error analysis result and the second error analysis result.

A method for diagnosing a speech recognition error, comprising:

• performing at least one first error analysis operation on a speech recognition result generated by a speech recognition component to provide at least one first error analysis result;
• performing at least one second error analysis operation on the speech recognition result to provide at least one second error analysis result;
• and
• based on a combination of at least the first error analysis result and the second error analysis result, determining at least one corrective action to at least partially increase an operability of at least one speech recognition operation of the speech recognition component.