Abstract: A method for context-aware translation is provided. The present invention may include receiving a program integrated information file (PII) associated with a graphical user interface object of with a software product. The present invention may also include indexing each element string within the PII file. The present invention may further include generating a base language general availability build of the graphical user interface object using the PII file. The present invention may also include retrieving a document object model (DOM) of each element within the base language general availability build. The present invention may further include creating a string relation table for the base language general availability build using the DOM for each element and each indexed element string within the PII file. The present invention may also include generating a string relation translation memory table for at least one language.

Abstract: A method and system for a translation manager system are described. The translation manager system allows a web translation application to insert the proper translations into web pages generated by the translation manager system. The translation manager system properly identifies how a page is reached by the user, as well as where in the page the user has selected to make their suggestion. The translation manager system uses key-locations to identify different areas where the user may make a suggestion and the web page may include multiple key-locations.

Abstract: Computing devices and methods for providing speech recognition data from one computing device to another device are disclosed. In one disclosed embodiment, audio input is received at a client device and processed to generate speech recognition data. An estimated confidence level is determined for a portion of the data, where the confidence level exceeds a predetermined confidence threshold corresponding to a valid result. At least one statistically improbable characteristic associated with the portion of data is identified. Based on identifying the statistically improbable characteristic, the portion of data is provided to a server computing device for evaluation.

Abstract: A computer-implemented method includes determining one or more information artifacts and determining at least one of one or more input properties or one or more content properties. The one or more input properties and the one or more content properties are each associated with the one or more information artifacts. The computer-implemented method further includes determining whether the one or more input information artifacts comprise one or more emotional indications based on at least one of the one or more input properties or the one or more content properties. The computer-implemented method further includes determining whether to perform one or more responsive actions based on the one or more emotional indications. A corresponding computer program product and computer system are also disclosed.

Abstract: A method and system for providing translation information are disclosed. The method for providing translation information includes: S1, receiving a source language statement inputted by a user, and acquiring a current target language statement according to the source language statement; S2, displaying the current target language statement and a preset control on a current interface; and S3, receiving an operation performed on the preset control from the user, and acquiring another target language statement according to the operation and displaying the other target language statement on the current interface. With the method, many translation results of one complete statement may be provided fast and conveniently without repeatedly selecting words or phrases from several candidate items, such that the user may view more translation results, thus improving the accuracy of translation and the user satisfaction level effectively.

Abstract: An apparatus for encoding a speech signal by determining a codebook vector of a speech coding algorithm is provided. The apparatus includes a matrix determiner for determining an autocorrelation matrix R, and a codebook vector determiner for determining the codebook vector depending on the autocorrelation matrix R. The matrix determiner is configured to determine the autocorrelation matrix R by determining vector coefficients of a vector r, wherein the autocorrelation matrix R includes a plurality of rows and a plurality of columns, wherein the vector r indicates one of the columns or one of the rows of the autocorrelation matrix R, wherein R(i, j)=r(|i?j|), wherein R(i, j) indicates the coefficients of the autocorrelation matrix R, wherein i is a first index indicating one of a plurality of rows of the autocorrelation matrix R, and wherein j is a second index indicating one of the plurality of columns of the autocorrelation matrix R.

Abstract: A method includes receiving, at a processor, a request to construct a word entry of a word. The method further includes collecting, by the processor, a user profile. The method further includes selecting, by the processor, one or more definition databases according to the user profile. The method further includes retrieving, by the processor, definitions of the word from the definition databases. The method further includes ranking, by the processor, the definitions retrieved from the definition databases.

Abstract: Disclosed are systems, methods, circuits and associated computer executable code for deep learning based natural language understanding, wherein training of one or more neural networks, includes: producing character strings inputs ‘noise’ on a per-character basis, and introducing the produced ‘noise’ into machine training character strings inputs fed to a ‘word tokenization and spelling correction language-model’, to generate spell corrected word sets outputs; feeding machine training word sets inputs, including one or more ‘right’ examples of correctly semantically-tagged word sets, to a ‘word semantics derivation model’, to generate semantically tagged sentences outputs. Upon models reaching a training ‘steady state’, the ‘word tokenization and spelling correction language-model’ is fed with input character strings representing ‘real’ linguistic user inputs, generating word sets outputs that are fed as inputs to the word semantics derivation model for generating semantically tagged sentences outputs.

Abstract: Aspects of the present disclosure involve a method for a voice trigger device that can be used to interrupt an externally connected system. The current disclosure also presents the architecture for the voice trigger device used for searching and matching an audio signature with a reference signature. In one embodiment a reverse matching mechanism is performed. In another embodiment, the reverse search and match operation is performed using an exponential normalization technique.

Abstract: Techniques disclose methods for providing voice-based web navigation through a cellular voice connection. A voice command a request to return content of a webpage having one or more topics is received via a cellular voice connection. One or more of the topics of the webpage that match the content specified in the request is identified. An audio indication of the content is returned via the cellular voice connection.

Abstract: Techniques disclose methods for providing voice-based web navigation through a cellular voice connection. A voice command a request to return content of a webpage having one or more topics is received via a cellular voice connection. One or more of the topics of the webpage that match the content specified in the request is identified. An audio indication of the content is returned via the cellular voice connection.

Abstract: Systems and methods for automatically generating at least one of facial expressions, body gestures, vocal expressions, or verbal expressions for a virtual agent based on emotion, mood and/or personality of a user and/or the virtual agent are provided. Systems and method for determining a user's emotion, mood and/or personality are also provided.

Abstract: Systems and methods for an online mediated language translation market are described. A language translation mediation (“LTM”) system may provide customers with the ability to request and receive language translation services on demand and/or in real-time. Language translation services may be provided by the language translation mediation system, for example via translators who know multiple languages, in exchange for a translation fee. A customer may request a translation of text, images, audio and/or video content from the LTM system, the LTM system routes the translation request to one or more translators who may perform the translation, and the LTM system provides one or more selected translations to the customer. In some embodiments the LTM system may determine a price for a translation and/or facilitate payment on behalf of, or from, the customer, to the translator who provided the translation for the customer.

Abstract: Audio encoding methods/terminals, audio decoding methods/terminals, and audio codec systems are provided. A plurality of audio signals that are continuous is obtained. it is determined whether each audio signal of the plurality of audio signals includes a designated signal type, according to an audio parameter of each audio signal. A marked audio encoding stream is obtained by performing a marking to each audio signal as having or not having the designated signal type. The marking is used, at a decoding terminal, to perform an enhancement-process to one or more audio signals having the designated signal type. The enhancement-process is not performed to audio signals that do not have the designated signal type.

Abstract: The present invention discloses an input method, including: receiving input end indication information sent by an input module, where the input end indication information indicates that input of a character or a word ends; obtaining a location of a cursor; identifying the input character or word forward from the location of the cursor until a first punctuation input before the character or the word is identified; using the identified character or word as a previous text, and querying a word library for a next text associated with the previous text; and outputting the associated next text to a display module for displaying. The input method provided in embodiments of the present invention is capable of associating a next text according to an input previous text for a user to select after the user presses an input end key, for example, the space key, to end the input of a character or a word, so that the input efficiency is increased.

Abstract: Disclosed herein are systems, methods, and non-transitory computer-readable storage media for detecting and correcting abnormal stress patterns in unit-selection speech synthesis. A system practicing the method detects incorrect stress patterns in selected acoustic units representing speech to be synthesized, and corrects the incorrect stress patterns in the selected acoustic units to yield corrected stress patterns. The system can further synthesize speech based on the corrected stress patterns. In one aspect, the system also classifies the incorrect stress patterns using a machine learning algorithm such as a classification and regression tree, adaptive boosting, support vector machine, and maximum entropy. In this way a text-to-speech unit selection speech synthesizer can produce more natural sounding speech with suitable stress patterns regardless of the stress of units in a unit selection database.

Abstract: A method for context-aware translation is provided. The present invention may include receiving a program integrated information file (PII) associated with a graphical user interface object of with a software product. The present invention may also include indexing each element string within the PII file. The present invention may further include generating a base language general availability build of the graphical user interface object using the PII file. The present invention may also include retrieving a document object model (DOM) of each element within the base language general availability build. The present invention may further include creating a string relation table for the base language general availability build using the DOM for each element and each indexed element string within the PII file. The present invention may also include generating a string relation translation memory table for at least one language.

Abstract: Controlling assistance information comprises determining a user mode based on computer input signals generated by a user. If the user is in a passive mode and assistance information is detected, the assistance information is disabled in response to detecting a hidden signal. The assistance information is then enabled if later a reset signal is detected. If the user is in passive mode and assistance information is not detected, the assistance information is enabled in response to detecting a trigger signal. If the user is in an active mode and assistance information is detected, the assistance information is disabled.

Abstract: Aspects relate to computer implemented methods, systems, and processes to automatically generate audio-based display indicia of media content including receiving, by a processor, a plurality of media content categories including at least one feature, receiving a plurality of categorized speech recognition algorithms, each speech recognition algorithm being associated with a respective one or more of the plurality of media content categories, determining a media content category of a current media content based on at least one feature of the current media content, selecting one speech recognition algorithm from the plurality of categorized speech recognition algorithms based on the determination of the media content category of the current media content, and applying the selected speech recognition algorithm to the current media content.

Abstract: A method can include receiving, from a user, a string of characters. The method can also include determining components of the string of characters. The components of the string of characters may include one or more graphemes that are related in the string of characters. The method can include determining universal phonetic representations for the components of the string of characters. The method can also include determining pronunciations for the universal phonetic representations. Additionally, the method can include constructing a pronunciation of the string of characters based at least partially on the pronunciations of the universal phonetic representations. Further, the method can include sending, to the user, a sound file representing the pronunciation of the string of characters.