Patent application number | Description | Published |
20090248422 | INTRA-LANGUAGE STATISTICAL MACHINE TRANSLATION - Training data may be provided, the training data including pairs of source phrases and target phrases. The pairs may be used to train an intra-language statistical machine translation model, where the intra-language statistical machine translation model, when given an input phrase of text in the human language, can compute probabilities of semantic equivalence of the input phrase to possible translations of the input phrase in the human language. The statistical machine translation model may be used to translate between queries and listings. The queries may be text strings in the human language submitted to a search engine. The listing strings may be text strings of formal names of real world entities that are to be searched by the search engine to find matches for the query strings. | 10-01-2009 |
20100121639 | Speech Processing - The described implementations relate to speech spelling by a user. One method identifies one or more symbols that may match a user utterance and displays an individual symbol for confirmation by the user. | 05-13-2010 |
20100312782 | PRESENTING SEARCH RESULTS ACCORDING TO QUERY DOMAINS - A query may be applied against search engines that respectively return a set of search results relating to various items discovered in the searched data sets. However, presenting numerous and varied search results may be difficult on mobile devices with small displays and limited computational resources. Instead, search results may be associated with search domains representing various information types (e.g., contacts, public figures, places, projects, movies, music, and books) and presented by grouping search results with associated query domains, e.g., in a tabbed user interface. The query may be received through an input device associated with a particular input domain, and may be transitioned to the query domain of a particular search engine (e.g., by recognizing phonemes of a voice query using an acoustic model; matching phonemes with query terms according to a pronunciation model; and generating a recognition result according to a vocabulary of an n-gram language model.) | 12-09-2010 |
20120316877 | DYNAMICALLY ADDING PERSONALIZATION FEATURES TO LANGUAGE MODELS FOR VOICE SEARCH - A dynamic exponential, feature-based, language model is continually adjusted per utterance by a user, based on the user's usage history. This adjustment of the model is done incrementally per user, over a large number of users, each with a unique history. The user history can include previously recognized utterances, text queries, and other user inputs. The history data for a user is processed to derive features. These features are then added into the language model dynamically for that user. | 12-13-2012 |
20140249799 | RELATIONAL SIMILARITY MEASUREMENT - Relational similarity measuring embodiments are presented that generally involve creating a relational similarity model that, given two pairs of words, is used to measure a degree of relational similarity between the two relations respectively exhibited by these word pairs. In one exemplary embodiment this involves creating a combined relational similarity model from a plurality of relational similarity models. This is generally accomplished by first selecting a plurality of relational similarity models, each of which measures relational similarity between two pairs of words, and each of which is trained or created using a different method or linguistic/textual resource. The selected models are then combined to form the combined relational similarity model. The combined model inputs two pairs of words and outputs a relational similarity indicator representing a measure the degree of relational similarity between the word pairs. | 09-04-2014 |
Patent application number | Description | Published |
20080281806 | SEARCHING A DATABASE OF LISTINGS - A database having listings rather than long documents is searched using a term frequency-inverse document frequency (Tf/Idf) algorithm. | 11-13-2008 |
20100076752 | Automated Data Cleanup - 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. | 03-25-2010 |
20100076765 | STRUCTURED MODELS OF REPITITION FOR SPEECH RECOGNITION - Described is a technology by which a structured model of repetition is used to determine the words spoken by a user, and/or a corresponding database entry, based in part on a prior utterance. For a repeated utterance, a joint probability analysis is performed on (at least some of) the corresponding word sequences as recognized by one or more recognizers) and associated acoustic data. For example, a generative probabilistic model, or a maximum entropy model may be used in the analysis. The second utterance may be a repetition of the first utterance using the exact words, or another structural transformation thereof relative to the first utterance, such as an extension that adds one or more words, a truncation that removes one or more words, or a whole or partial spelling of one or more words. | 03-25-2010 |
20110224982 | AUTOMATIC SPEECH RECOGNITION BASED UPON INFORMATION RETRIEVAL METHODS - Described is a technology in which information retrieval (IR) techniques are used in a speech recognition (ASR) system. Acoustic units (e.g., phones, syllables, multi-phone units, words and/or phrases) are decoded, and features found from those acoustic units. The features are then used with IR techniques (e.g., TF-IDF based retrieval) to obtain a target output (a word or words). Also described is the use of IR techniques to provide a full large vocabulary continuous speech (LVCSR) recognizer | 09-15-2011 |
20140037218 | THREE-DIMENSIONAL OBJECT BROWSING IN DOCUMENTS - A document that includes a representation of a two-dimensional (2-D) image may be obtained. A selection indicator indicating a selection of at least a portion of the 2-D image may be obtained. A match correspondence may be determined between the selected portion of the 2-D image and a three-dimensional (3-D) image object stored in an object database, the match correspondence based on a web crawler analysis result. A 3-D rendering of the 3-D image object that corresponds to the selected portion of the 2-D image may be initiated. | 02-06-2014 |
20140067368 | DETERMINING SYNONYM-ANTONYM POLARITY IN TERM VECTORS - A document-term matrix may be generated based on a corpus. A term representation matrix may be generated based on modifying a plurality of elements of the document-term matrix based on antonym information included in the corpus. Similarities may be determined based on a plurality of elements of the term representation matrix. | 03-06-2014 |
20140156260 | GENERATING SENTENCE COMPLETION QUESTIONS - The subject disclosure is directed towards automated processes for generating sentence completion questions based at least in part on a language model. Using the language model, a sentence is located, and alternates for a focus word (or words) in the sentence are automatically provided. Also described is automated filtering candidate sentences to locate the sentence, filtering the alternates based upon elimination criteria, scoring sentences with the correct word and as modified the alternates, and ranking the alternates. Manual selection may be used along with the automated processes. | 06-05-2014 |
Patent application number | Description | Published |
20080262995 | Multimodal rating system - A method of communicating information about a product evaluation between a system having a data store and a wireless client device is discussed. The method includes receiving a signal representative of an audible indication from the client device via a wireless communication link identifying the product about which evaluation information is to be communicated. The method further includes comparing an indication of the signal to data in the data store in response to match the indication with a portion of the data and communicating evaluation information between the wireless client device and the system. | 10-23-2008 |
20080298562 | Voice aware demographic personalization - 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. | 12-04-2008 |
20110131046 | FEATURES FOR UTILIZATION IN SPEECH RECOGNITION - A computer-implemented speech recognition system described herein includes a receiver component that receives a plurality of detected units of an audio signal, wherein the audio signal comprises a speech utterance of an individual. A selector component selects a subset of the plurality of detected units that correspond to a particular time-span. A generator component generates at least one feature with respect to the particular time-span, wherein the at least one feature is one of an existence feature, an expectation feature, or an edit distance feature. Additionally, a statistical speech recognition model outputs at least one word that corresponds to the particular time-span based at least in part upon the at least one feature generated by the feature generator component. | 06-02-2011 |
20140059078 | SEMANTIC QUERY LANGUAGE - Various technologies described herein pertain to executing a mixed query to search a database retained in a data repository. The mixed query includes a regular expression, which is a pattern of elements, and a semantic constraint. The elements in the regular expression include a first wildcard, where the semantic constraint restricts a meaning of the first wildcard. Moreover, the elements in the regular expression include explicit lexical constraint(s) and/or disparate wildcard(s). For instance, semantic constraint(s) can restrict meaning(s) of the disparate wildcard(s). The mixed query is executed to retrieve results that match the pattern of the elements in the regular expression and satisfy the semantic constraint(s). | 02-27-2014 |
20150066496 | ASSIGNMENT OF SEMANTIC LABELS TO A SEQUENCE OF WORDS USING NEURAL NETWORK ARCHITECTURES - Technologies pertaining to slot filling are described herein. A deep neural network, a recurrent neural network, and/or a spatio-temporally deep neural network are configured to assign labels to words in a word sequence set forth in natural language. At least one label is a semantic label that is assigned to at least one word in the word sequence. | 03-05-2015 |
20150161101 | RECURRENT CONDITIONAL RANDOM FIELDS - Recurrent conditional random field (R-CRF) embodiments are described. In one embodiment, the R-CFR receives feature values corresponding to a sequence of words. Semantic labels for words in the sequence of words are then generated and each label is assigned to the appropriate one of the words in the sequence of words. The R-CRF used to accomplish these tasks includes a recurrent neural network (RNN) portion and a conditional random field (CRF) portion. The RNN portion receives feature values associated with a word in the sequence of words and outputs RNN activation layer activations data that is indicative of a semantic label. The CRF portion inputs the RNN activation layer activations data output from the RNN for one or more words in the sequence of words and outputs label data that is indicative of a separate semantic label that is to be assigned to each of the words. | 06-11-2015 |