Abstract: Systems and methods consistent with the present invention determine whether to accept one of a plurality of intermediate recognition results output by a speech recognition system as a final recognition result. The system first combines a plurality of speech rejection features into a feature function in which weights are assigned to each rejection feature in accordance with a recognition accuracy of each rejection feature. Feature values are then calculated for each of the rejection features using the plurality of intermediate recognition results. The system next computes the feature function according to the calculated feature values to determine a rejection decision value. Finally, one of the plurality of intermediate recognition results is accepted as the final recognition result according to the rejection decision value.

Abstract: The invention relates to a method and apparatus for automatically generating probability tables (histograms) for a speech recognition dictionary for use in a speech recognition system from a listing containing call records. The method comprises the step of generating histograms representing the probabilities of localities being requested based on the calling pattern collected on the field by either a human operator or via an automatic process during calls. The method is particularly useful for generating an a priori advisor for a speech recognition dictionary used in an automated system for locality recognition.

Abstract: The invention relates to an automated directory assistance system that utilizes a heuristics model for predicting the most likely requested number. Each orthography link in the speech recognition dictionary pointing toward an entry in the white pages is associated with a data structure that provides a probability value of that link pointing toward the telephone number intended by the user on the basis of locality information specified by the user of the automated directory assistance system.

Abstract: The invention relates to a method and an apparatus for adding a new entry to a speech recognition dictionary, more particularly to a system and method for generating transcriptions from multiple utterances of a given word. The novel method and apparatus automatically transcribes several training utterances into transcriptions without knowledge of the orthography of the word being added. It also provides a method and apparatus for transcribing multiple utterances into a single transcription that can be added to a speech recognition dictionary. In a first step, each utterance is analyzed individually to get their respective acoustic characteristics. Following this, these characteristics are combined to generate a set of the most likely transcriptions using the acoustic information obtained from each of the training utterances.

Abstract: The invention relates to a method and apparatus for grouping orthographies in a speech recognition dictionary to reduce false rejection. In a typical speech recognition system, the process of speech recognition consists of scanning the vocabulary database by using a fast match algorithm to find the top N orthography groups. In a second pass the orthographies in the selected groups are re-scored using more precise likelihoods. The top orthographies in the top two groups are then processed by a rejection algorithm to find if they are sufficiently distinct from one another. In the affirmative the top choice candidate is accepted, otherwise the entire procedure is terminated. The novel method comprises the steps of grouping confusable orthographies together to reduce the possibility of false rejection.

Abstract: The invention relates to a method and apparatus for automatically generating a speech recognition vocabulary for a speech recognition system from a listing that contains a number of entries, each entry containing a multi-word identification data that distinguishes that entry from other entries in the list. The method comprises the steps of creating for each entry in the listing a plurality of orthographies in the speech recognition vocabulary that are formed by combining selected words from the entry. The words combination is effected by applying a heuristics model that mimics the way users formulate requests to the automated directory assistance system. The method is particularly useful for generating speech recognition vocabularies for automated directory assistance systems.