Abstract: A method for adaptive automatic error and mismatch correction is disclosed for use with a system having an automatic error and mismatch correction learning module, an automatic error and mismatch correction model, and a classifier module. The learning module operates by receiving pairs of documents, identifying and selecting effective candidate errors and mismatches, and generating classifiers corresponding to these selected errors and mismatches. The correction model operates by receiving a string of interpreted speech into the automatic error and mismatch correction module, identifying target tokens in the string of interpreted speech, creating a set of classifier features according to requirements of the automatic error and mismatch correction model, comparing the target tokens against the classifier features to detect errors and mismatches in the string of interpreted speech, and modifying the string of interpreted speech based upon the classifier features.

Abstract: The present invention pertains to a system and method for the tokenization of text. The featurizer may be configured to receive input text and convert the input text into tokens. According to one aspect of the invention, the tokens may include only one type of character, the characters selected from the group consisting of letters, numbers, and punctuation. The tokenizer may also include a classifier. The classifier may be configured to receive the tokens from the featurizer. Furthermore, the classifier may be configured to analyze the tokens received from the featurizer to determine if the tokens may be input into a predetermined classification model using a preclassifier. If one of the tokens passes the preclassifier, then the token is classified using the predetermined classification model. Additionally, according to a first aspect of the invention, the tokenizer may also include a finalizer. The finalizer may be configured to receive the tokens and may be configured to produce a final output.

Abstract: A system and method for a speech recognition technology that allows language models for a particular language to be customized through the addition of alternate pronunciations that are specific to the accent of the dictator, for a subset of the words in the language model. The system includes the steps of identifying the pronunciation differences that are best handled by modifying the pronunciations of the language model, identifying target words in the language model for pronunciation modification, and creating a accented speech file used to modify the language model.

Abstract: 5 A system and method may be disclosed for facilitating the site-specific customization of automated speech recognition systems by providing a customization client for site-specific individuals to update and modify language model input files and post processor input files. In customizing the input files, the customization client may provide a graphical user interface for facilitating the inclusion of words specific to a particular site. The customization client may also be configured to provide the user with a series of formatting rules for controlling the appearance and format of a document transcribed by an automated speech recognition system.