Abstract: A multi-modal search system (and corresponding methodology) that employs wildcards is provided. Wildcards can be employed in the search query either initiated by the user or inferred by the system. These wildcards can represent uncertainty conveyed by a user in a multi-modal search query input. In examples, the words “something” or “whatchamacallit” can be used to convey uncertainty and partial knowledge about portions of the query and to dynamically trigger wildcard generation.

Abstract: Architecture that provides the capability to identify which parts (terms and phrases) of a voice query have been covered by predefined phrase templates, and then to concatenate matching phrase templates into a new paraphrased query. A match-drop-continue algorithm is disclosed that progressively masks out the portions (phrases, terms) of the query matched to the phrase templates. Ultimately, the matched phrase templates are accumulated and organized together dynamically into a rephrased version of the original voice query. A user interface is provided that allows the user to confirm/summarize the multiple concepts in a progressive manner.

Abstract: Described is the use of utterance classification based methods and other machine learning techniques to provide a telephony application or other voice menu application (e.g., an automotive application) that need not use Context-Free-Grammars to determine a user's spoken intent. A classifier receives text from an information retrieval-based speech recognizer and outputs a semantic label corresponding to the likely intent of a user's speech. The semantic label is then output, such as for use by a voice menu program in branching between menus. Also described is training, including training the language model from acoustic data without transcriptions, and training the classifier from speech-recognized acoustic data having associated semantic labels.

Abstract: The presentation of location information to a user that is distracted by traveling can result in the user quickly forgetting, or never even comprehending, key parts of the location information, such as the street number. Identification can be made of intersections and points of interest near the user's destination, which can then be provided instead of, or in addition to, the address, thereby increasing user comprehension and retention, especially when distracted. Map data can be parsed into addresses, intersections and points of interest databases. These databases can be accessed to identify proximate intersections and points of interest, which can then be filtered and subsequently ranked to identify one intersection, one point of interest, or both, that can be presented to the user to aid the user in comprehending and retaining the location information even when distracted.

Abstract: An answering machine detection module is used to determine whether a call recipient is an actual person or an answering machine. The answering machine detection module includes a speech recognizer and a call analysis module. The speech recognizer receives an audible response of the call recipient to a call. The speech recognizer processes the audible response and provides an output indicative of recognized speech. The call analysis module processes the output of the speech recognizer to generate an output indicative of whether the call recipient is a person or an answering machine.

Abstract: A method for managing an interaction of a calling party to a communication partner is provided. The method includes automatically determining if the communication partner expects DTMF input. The method also includes translating speech input to one or more DTMF tones and communicating the one or more DTMF tones to the communication partner, if the communication partner expects DTMF input.

Abstract: In one embodiment, the present system recognizes a user's speech input using an automatically generated probabilistic context free grammar for street names that maps all pronunciation variations of a street name to a single canonical representation during recognition. A tokenizer expands the representation using position-dependent phonetic tokens and an intersection classifier classifies an intersection, despite the presence of recognition errors and incomplete street names.

Abstract: A statistical language model is trained for use in a directory assistance system using the data in a directory assistance listing corpus. Calculations are made to determine how important words in the corpus are in distinguishing a listing from other listings, and how likely words are to be omitted or added by a user. The language model is trained using these calculations.

Abstract: A voice interaction system is configured to analyze an utterance and identify inherent attributes that are indicative of a demographic characteristic of the system user that spoke the utterance. The system then selects and presents a personalized response to the user, the response being selected based at least in part on the identified demographic characteristic. In one embodiment, the demographic characteristic is one or more of the caller's age, gender, ethnicity, education level, emotional state, health status and geographic group. In another embodiment, the selection of the response is further based on consideration of corroborative caller data.

Abstract: A directory assistance system includes a directory database and a search engine. The search engine is configured to search the directory database for a first set of residential listings based on at least one first search term. A second search term is received that is related to a cohabitant of the listing to be found. At least one search result is selected that satisfies the second search term.

Abstract: A statistical language model is trained for use in a directory assistance system using the data in a directory assistance listing corpus. Calculations are made to determine how important words in the corpus are in distinguishing a listing from other listings, and how likely words are to be omitted or added by a user. The language model is trained using these calculations.

Abstract: A method of forming a shareable filler model (shareable model for garbage words) from a word n-gram model is provided. The word n-gram model is converted into a probabilistic context free grammar (PCFG). The PCFG is modified into a substantially application-independent PCFG, which constitutes the shareable filler model.

Abstract: A computer-implemented method is disclosed for improving the accuracy of a directory assistance system. The method includes constructing a prefix tree based on a collection of alphabetically organized words. The prefix tree is utilized as a basis for generating splitting rules for a compound word included in an index associated with the directory assistance system. A language model check and a pronunciation check are conducted in order to determine which of the generated splitting rules are mostly likely correct. The compound word is split into word components based on the most likely correct rule or rules. The word components are incorporated into a data set associated with the directory assistance system, such as into a recognition grammar and/or the index.

Abstract: A process for collecting the identity of a telephone caller is disclosed. In one embodiment, a personalized Context Free Grammar (CFG) is created for each potential call recipient, and is configured to support identification of incoming callers utilizing voice recognition. Each CFG incorporates an indication of high probability callers and probability weights in each CFG are altered accordingly. When a recipient receives a call, the relevant CFG is applied in association with a voice recognition application to enable at least a preliminary identification of the caller. In accordance with another embodiment, the caller confirms identifications. In accordance with one embodiment, standard caller-ID functionality is utilized if possible at least to assist in the caller identification process. In accordance with still another embodiment, voice recognition enhanced caller identification is utilized to provide intelligent call routing functionality.

Abstract: A speech recognition application including a recognition module configured to receive input utterances and an application module configured to select a recognition from the speech recognition module using output from a first iteration to select a recognition result for a second iteration. In one embodiment, the application module eliminates a previous rejected recognition result or results from the N-Best list for recognition. In another embodiment, the application module rescores N-Best entries based upon N-Best lists or information from another iteration. In another illustrated embodiment, the application module uses a limited grammar from a current N-Best list for subsequent recognition, for example for rerecognition using a recorded input from a previous iteration.

Abstract: An automated “Voice Search Message Service” provides a voice-based user interface for generating text messages from an arbitrary speech input. Specifically, the Voice Search Message Service provides a voice-search information retrieval process that evaluates user speech inputs to select one or more probabilistic matches from a database of pre-defined or user-defined text messages. These probabilistic matches are also optionally sorted in terms of relevancy. A single text message from the probabilistic matches is then selected and automatically transmitted to one or more intended recipients. Optionally, one or more of the probabilistic matches are presented to the user for confirmation or selection prior to transmission. Correction or recovery of speech recognition errors avoided since the probabilistic matches are intended to paraphrase the user speech input rather than exactly reproduce that speech, though exact matches are possible.

Abstract: A language processing system may determine a display form of a spoken word by analyzing the spoken form using a language model that includes dictionary entries for display forms of homonyms. The homonyms may include trade names as well as given names and other phrases. The language processing system may receive spoken language and produce a display form of the language while displaying the proper form of the homonym. Such a system may be used in search systems where audio input is converted to a graphical display of a portion of the spoken input.

Abstract: The described implementations relate to automated data cleanup. One system includes a language model generated from language model seed text and a dictionary of possible data substitutions. This system also includes a transducer configured to cleanse a corpus utilizing the language model and the dictionary.

Abstract: A method of generating an optimized grammar, for use in speech recognition, from a data set or big list of items, is disclosed. The method includes the steps of obtaining a tree representing items in the data set, and generating the grammar using the tree. The tree or tree data structure representing items in the data set is a simulated recognition search tree, representing items in the data set, which can be automatically generated from the data set.

Abstract: A method of providing information to a user in a telephone interactive system includes receiving a new call. A comparison is then made between an identifier associated with the new call with stored call information pertaining to previous calls. If the identifier associated with the new call matches an identifier associated with a previous call, a subsequent action taken in the new call is based on context information stored from the previous call.