Abstract: Techniques and technologies for diagnosing speech recognition errors are described. In an example implementation, a system for diagnosing speech recognition errors may include an error detection module configured to determine that a speech recognition result is least partially erroneous, and a recognition error diagnostics module. The recognition error diagnostics module may be configured to (a) perform a first error analysis of the at least partially erroneous speech recognition result to provide a first error analysis result; (b) perform a second error analysis of the at least partially erroneous speech recognition result to provide a second error analysis result; and (c) determine at least one category of recognition error associated with the at least partially erroneous speech recognition result based on a combination of the first error analysis result and the second error analysis result.

Abstract: A speech recognition system includes a feature extraction component that receives a speech signal and extracts feature vectors from the speech signal. Also included, is a decoder having a speech acoustic model, a feature modification component, and a comparison component. The feature modification component changes the feature vectors, using adaptation data and prior data, to more closely match. the speech acoustic model. The comparison component utilizes the modified feature vectors and the speech acoustic model to recognize the speech signal.