Abstract:
Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.
Abstract:
A system may be configured to receive a query; identify an object and a verb associated with the query; obtain information indicating a quantity of occurrences, in one or more documents, of the object in a sentence that may include the verb, or a quantity of occurrences, in one or more documents, of one or more terms, which are related to the object, in a sentence that may include the verb; generate a confidence score that may indicate a probability that the query seeks a result relating to a name of a person; identify a set of documents that are responsive to the query; determine that the confidence score satisfies a threshold; identify one or more documents, of the set of documents, that are associated with one or more names of people; select a particular document, of the set of documents; and output information regarding the selected particular document.
Abstract:
An embodiment may receive a question at a computing device; obtain a search result set in response to the question; identify, using the computing device, one or more entities that are associated with at least one document referenced by the search result set; select, using the computing device, one or more relevant entities identified as being associated with (i) documents referenced by the search result set and (ii) the question; and output, using the computing device, an answer to the question based at least on the selected one or more entities.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for resolving ambiguity in received voice queries. An original voice query is received following one or more earlier voice queries, wherein the original voice query includes a pronoun or phrase. In one implementation, a plurality of acoustic parameters is identified for one or more words in the original voice query. A concept represented by the pronoun is identified based on the plurality of acoustic parameters, wherein the concept is associated with a particular query of the one or more earlier queries. The concept is associated with the pronoun. Alternatively, a concept may be associated with a phrase by using grammatical analysis of the query to relate the phrase to a concept derived from a prior query.
Abstract:
An embodiment may receive a question at a computing device; obtain a search result set in response to the question; identify, using the computing device, one or more entities that are associated with at least one document referenced by the search result set; select, using the computing device, one or more relevant entities identified as being associated with (i) documents referenced by the search result set and (ii) the question; and output, using the computing device, an answer to the question based at least on the selected one or more entities.
Abstract:
A system may be configured to receive a query; identify an object and a verb associated with the query; obtain information indicating a quantity of occurrences, in one or more documents, of the object in a sentence that may include the verb, or a quantity of occurrences, in one or more documents, of one or more terms, which are related to the object, in a sentence that may include the verb; generate a confidence score that may indicate a probability that the query seeks a result relating to a name of a person; identify a set of documents that are responsive to the query; determine that the confidence score satisfies a threshold; identify one or more documents, of the set of documents, that are associated with one or more names of people; select a particular document, of the set of documents; and output information regarding the selected particular document.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying queries. A query that includes one or more query terms is received. One or more entity identifiers are extracted from one or more search results that are responsive to the query. One or more of the query terms are compared with the extracted entity identifiers. Based on comparing the query terms with the extracted entity identifiers, the query is classified as an entity-triggering query or as a description-triggering query.
Abstract:
Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a dialog system using user feedback. According to one implementation, a method includes receiving, by a dialog engine, a first input that specifies a question; providing, by the dialog engine, an answer to the question; receiving, by the dialog engine, a second input; and determining, by the dialog engine, that the second input is classified as feedback to the answer, then determining a feedback score associated with the second input.