A system and method for fast concept search in multiple documents where the concept is expressed by plurality of words, all of which have to be in the same sentence and within specified range. The system automatically finds equivalent expressions of the same concept, and returns as search results all documents in which the concept is contained.

The present invention relates to a searching device, searching method, and program whereby searching for a word string corresponding to input voice can be performed in a robust manner. A voice recognition unit 11 subjects an input voice to voice recognition. A matching unit 16 performs matching, for each of multiple word strings for search results which are word strings that are to be search results for word strings corresponding to the input voice, of a pronunciation symbol string for search results, which is an array of pronunciation symbols expressing pronunciation of the word string search result, and a recognition result pronunciation symbol string which is an array of pronunciation symbols expressing pronunciation of the voice recognition results of the input voice. An output unit 17 outputs a search result word string which is the result of searching the word strings corresponding to the input voice from the multiple word strings for search results, based on the matching results of the pronunciation symbol string for search results and the recognition result pronunciation symbol string. The present invention can be applied in the case of performing voice searching, for example.

A wake-up word recognition training system includes: a sentence database, storing a plurality of sentences and a phoneme sequence and a speech signal corresponding to each of the sentences; a phoneme disassembly module, disassembling a wake-up word inputted from the outside to obtain a wake-up word phoneme sequence; a phoneme analysis module, matching the wake-up word phoneme sequence to the sentences and/or phoneme sequences thereof, to obtain wake-up word part-of-speech sentences and non-wake-up word part-of-speech sentences; a sentence classification module, dividing the sentences in the sentence database into the wake-up word part-of-speech sentences and the non-wake-up word part-of-speech sentences according to a comparison result of the phoneme comparison module; and a wake-up word recognition module, obtaining speech signal fragments of the wake-up word and a non-wake-up word according to a phoneme combination of the wake-up word part-of-speech sentences and the non-wake-up word part-of-speech sentences.

Systems, apparatuses, and methods are provided for identifying a corresponding string stored in memory based on an incomplete input string. A system can analyze and produce phonetic and distance metrics for a plurality of strings stored in memory by comparing the plurality of strings to an incomplete input string. These similarity metrics can be used as the input to a machine learning model, which can quickly and accurately provide a classification. This classification can be used to identify a string stored in memory that corresponds to the incomplete input string.

In one example of the disclosure, a communication apparatus includes a first microphone. The communication apparatus is to be wirelessly and contemporaneously connected to a set of microphones including the first microphone. The communication apparatus is to receive microphone data from each microphone of the set of microphones, wherein the microphone data is indicative of a user spoken phrase captured by the set of microphones. The communication apparatus is to establish based on the received microphone data a selected microphone from among the set of microphones.

The present invention relates to an in-document search method and device for a query vector, and an object of the present invention is to improve the accuracy of a response by generating sentence data corresponding to data in a table form stored in database. The in-document search method for a query vector includes a step A of receiving a user query from a user terminal, a step B of generating a user query vector for the user query, a step C of extracting candidate table data based on the user query vector in a data storage module, a step D of searching for a response corresponding to the user query vector in the candidate table data, and a step E of providing the response to the user terminal.

Name matching using enhanced name keys is provided by receiving and parsing a queried name into name phrase(s), building a name key for the queried name, the name key for identifying matches between the queried name and candidate names in a database, and the name key including name phrase digraph bitmap signature(s) for the queried name, variant code(s) for the queried name, and pseudo-phonetic name phrase digraph bitmap signature(s) for the queried name, and performing a name matching comparison that includes comparing the queried name to each candidate name of the candidate names in the database, in which the built name key for the queried name is compared to a name key for the candidate name.

This application provides information processing methods, terminal devices, and distributed networks. In an implementation, after determining target information including at least one piece of text information and at least one piece of non-text information, a terminal device may determine, based on a predetermined playing speed and a predetermined time, at least one first location associated with at least one piece of non-text information. Text-to-speech is sequentially performed on the at least one piece of text information, to obtain and sequentially play speech information respectively corresponding to the at least one piece of text information. In response to speech information corresponding to first text information being played, target non-text information is sent to a second terminal device, so that the second terminal device displays the target non-text information.

Methods, apparatus, systems, and computer-readable media are provided for providing context specific schema files that allow an automated assistant to broker human-to-computer dialogs between a user and an application that is separate from the automated assistant. The context specific schema file can provide the automated assistant with sufficient data to be responsive to user queries without necessarily communicating with a remote device, such as a server. Multiple different context specific schema files can be made available to the automated assistant according to a context in which a user is interacting with the automated assistant. In this way, latency otherwise exhibited by the automated assistant can be mitigated by providing the automated assistant with the information needed to respond to a user without continually retrieving the information over a network.

A sentence structure vectorization device includes processing circuitry to generate a plurality of morphemes by performing morphological analysis on an input sentence; to generate a dependence structure graph regarding the plurality of morphemes by performing dependency parsing on the plurality of morphemes; and to generate a sentence structure vector by extracting a plurality of pieces of partial structure information from the dependence structure graph and converting a morpheme string corresponding to the plurality of pieces of partial structure information into a numerical sequence.