Abstract: Mechanisms are provided for customizing responses to future questions based on identified anomalies in user profile information. An automated dialogue system monitors information associated with a plurality of entities, where the information includes quantities for variable values associated with the entities. The automated dialogue system, in response to determining that a quantity of a variable value associated with an entity in the plurality of entities has changed by an amount equal to or exceeding a corresponding threshold value, generates response information associated with a quantity of the variable value and an entity to respond to at least one future question. In addition, the automated dialogue system stores the responsive information in association with the entity for later retrieval in response to initiation of a dialogue session with the automated dialogue system. Time thresholds may be established for determining when to stop using the responsive information for responding to questions.

Abstract: Methods and systems for speech recognition are disclosed. In one aspect, a method includes receiving an input signal representing spoken words, identifying individual words in the input signal, building a plurality of word sets based on the individual words, generating a partial result based on at least one of the plurality of word sets, receiving an additional input signal subsequent to the generation of the partial result, identifying an additional word from the additional input, detecting a semantic delimiter based on at least one of the plurality of word sets and the additional word, and in response to the detection, generating a response to the input signal based at least in part, on the partial result and the semantic delimiter.

Abstract: A method includes that for each model from multiple models, evaluating a model prediction accuracy based on a dataset of a user over a first time duration. The dataset includes a sequence of actions with corresponding contexts based on electronic device interactions. Each model is trained to predict a next action at a time point within the first time duration, based on a first behavior sequence over a first time period from the dataset before the time point, a second behavior sequence over a second time period from the dataset before the time point, and context at the time point. A model is selected from the multiple models based on its model prediction accuracy for the user based on a domain. An action to be initiated at a later time using an electronic device of the user is recommended using the selected model during a second time duration.

Abstract: The present disclosure provides a method and a device for displaying multi-language typesetting, a browser, a terminal and a computer readable storage medium. The method includes: obtaining a text to be typeset; identifying embedded language content in a principal language text of the text to be typeset, wherein the embedded language content comprises at least one non-principal language content embedded in the principal language text; determining replacement content of the embedded language content, wherein the replacement content comprises a principal language text corresponding to the embedded language content or an abbreviation of a non-principal language text in the embedded language content; and replacing the embedded language content with the replacement content.

Abstract: Provided are methods, systems, and apparatuses for detecting, processing, and responding to audio signals, including speech signals, within a designated area or space. A platform for multiple media devices connected via a network is configured to process speech, such as voice commands, detected at the media devices, and respond to the detected speech by causing the media devices to simultaneously perform one or more requested actions. The platform is capable of scoring the quality of a speech request, handling speech requests from multiple end points of the platform using a centralized processing approach, a de-centralized processing approach, or a combination thereof, and also manipulating partial processing of speech requests from multiple end points into a coherent whole when necessary.

Abstract: A speech synthesis dictionary delivery device that delivers a dictionary for performing speech synthesis to terminals, comprises a storage device for speech synthesis dictionary database that stores a first dictionary which includes an acoustic model of a speaker and is associated with identification information of the speaker, that stores a second dictionary which includes an acoustic model generated using voice data of a plurality of speakers, and that stores parameter sets of the speakers to be used with the second dictionary and which are associated with identification information of the speakers, a processor that determines one of the first dictionary and the second dictionary, which should be used in the terminal for a specified speaker, and an input output interface (I/F) that receives the identification information of a speaker transmitted from the terminal and then delivers at least one of a first dictionary, the second dictionary, and a parameter set of the second dictionary, on the basis of the rec

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: Examples of multi-user configuration are disclosed. An example method includes, at an electronic device: receiving a request; and in response to the request: if the voice input does not match a voice profile associated with an account associated with the electronic device: causing output of first information based on the request using a first account associated with the electronic device; if a setting of the electronic device has a first state, causing update of account data of the first account based on the request; and if the setting has a second state, forgoing causing update of the account data; and if the voice input matches a voice profile associated with an account associated with the electronic device: causing output of the first information using the account associated with the matching voice profile; and causing update of account data of the account based on the request.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for speech recognition. One method includes obtaining an input acoustic sequence, the input acoustic sequence representing one or more utterances; processing the input acoustic sequence using a speech recognition model to generate a transcription of the input acoustic sequence, wherein the speech recognition model comprises a domain-specific language model; and providing the generated transcription of the input acoustic sequence as input to a domain-specific predictive model to generate structured text content that is derived from the transcription of the input acoustic sequence.

Abstract: A voice interaction apparatus acquires a speech signal indicative of a speech sound, identifies a series of pitches of the speech sound from the speech signal, and causes a reproduction device to reproduce a response voice of pitches controlled in accordance with the lowest pitch of the pitches identified during a tailing section proximate to an end point within the speech sound.

Abstract: An intent classification method and a system for realizing the intent classification method are provided. The intent classification method can be used for determining an intent class of a sentence input in a language containing information-bearing characters, such as Chinese. The method specifically comprises a step of obtaining at least one set of word embeddings and character embeddings from the sentence input to thereby generate at least one set of integrated word-character embeddings, and a step of determining an intent class corresponding to the sentence input based on the at least one set of integrated word-character embeddings. Herein, each of the at least one set of integrated word-character embeddings corresponds to one of the at least one set of word embeddings and character embeddings.

Abstract: A computing device is disclosed which includes a processor and non-transient memory operably connected to the processor. The non-transient memory includes instructions that, when executed by the processor cause the processor to extract a plurality of sub-strings from a character string, analyze each sub-string for compliance with each of several field definitions, where each of the field definitions corresponds to a field in a digital form, and populate some of the fields in the digital form based on the analysis of each sub-string for compliance with the field definitions.

Abstract: A natural language processing system has a hierarchy of user intents related to a domain of interest, the hierarchy having specific intents corresponding to leaf nodes of the hierarchy, and more general intents corresponding to ancestor nodes of the leaf nodes. The system also has a trained understanding model that can classify natural language utterances according to user intent. When the understanding model cannot determine with sufficient confidence that a natural language utterance corresponds to one of the specific intents, the natural language processing system traverses the hierarchy of intents to find a more general user intent that is related to the most applicable specific intent of the utterance and for which there is sufficient confidence. The general intent can then be used to prompt the user with questions applicable to the general intent to obtain the missing information needed for a specific intent.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimized graph traversal are disclosed. In one aspect, a method includes the actions of receiving a given phrase that is input through a user interface by a digital component provider. The actions further include determining an entity that is being referred to by the given phrase. The actions further include identifying properties of the entity. The actions further include selecting a subset of the properties that were identified for the entity. The actions further include identifying additional phrases. The actions further include updating the user interface to present at least some of the additional phrases with programmatic controls that assign one or more of the additional phrase as distribution criteria for digital components of the digital component provider in response to activation of the programmatic controls.

Abstract: A method is presented for error correction of tabular data in document conversion. The method includes identifying errors from tabular data transformation by employing an error/invalidation checking module and correcting the identified errors from the tabular data transformation by employing an error correction module. The error correction module includes identifying a main structure pattern from common row structures, concatenating separate keywords according to natural language processing models employing training data obtained from a plurality of candidate tabular data, adjusting cells in the tabular data based on a domain-specific knowledge database including the training data in combination with linguistic and semantic knowledge, merging partial tabular data pieces, and generating an adjusted table as output on a display of a computing device.

Abstract: A system to dynamically update presentations based on context classification of voice inputs, comprising: a storage device and a processor communicatively coupled to the storage device, wherein the processor executes application code instructions that are stored in the storage device to cause the system to: display a first graphical user interface associated with a first context via a user interface, obtain a first voice input, determine one or more first terms from the first voice input, determine that the first voice input is related to a first context based on the one or more first terms, and in response to determining that the first voice input is related to the first context: modify the first graphical user interface associated with the first context and display the modified first graphical user interface associated with the first context via the user interface.

Abstract: Exemplary embodiments relate to methods, mediums, and systems for managing a conversation. In an embodiment, a computer-implemented input interface is provided to receive an input comprising information in natural language. A dialog manager is configured to determine an intent of the input, determine information to fulfill the intent, and identify one or both of information available to the dialog manager or information that is unavailable to the dialog manager. A conversational understanding document documents the intent and the identified information. An output interface forwards the conversational understanding document towards a task completion handler separate and distinct from the dialog manager. Other embodiments are described and claimed.

Abstract: Embodiments of the present disclosure disclose an artificial intelligence based method and apparatus for classifying a voice-recognized text. A specific embodiment of the method includes: acquiring a current interactive text of a voice query from a user; analyzing the current interactive text using a lexical analyzer to obtain a current lexical structure; determining whether the current lexical structure matches a template of a category in a classifier; and classifying, if the current lexical structure matches the template of the category in the classifier, the current interactive text corresponding to the current lexical structure into the category belonging to the matched template. The embodiment can fast classify texts, effectively reduce the magnitude of manually annotated texts, and improve the annotation efficiency in intelligent voice interaction services.

Abstract: Systems and processes for rule-based natural language processing are provided. In accordance with one example, a method includes, at an electronic device with one or more processors, receiving a natural-language input; determining, based on the natural-language input, an input expression pattern; determining whether the input expression pattern matches a respective expression pattern of each of a plurality of intent definitions; and in accordance with a determination that the input expression pattern matches an expression pattern of an intent definition of the plurality of intent definitions: selecting an intent definition of the plurality of intent definitions having an expression pattern matching the input expression pattern; performing a task associated with the selected intent definition; and outputting an output indicating whether the task was performed.

Abstract: Systems, methods, and devices for recognizing a user are disclosed. A speech-controlled device captures a spoken utterance, and sends audio data corresponding thereto to a server. The server determines content sources storing or having access to content responsive to the spoken utterance. The server also determines multiple users associated with a profile of the speech-controlled device. Using the audio data, the server may determine user recognition data with respect to each user indicated in the speech-controlled device's profile. The server may also receive user recognition confidence threshold data from each of the content sources. The server may determine user recognition data associated that satisfies (i.e., meets or exceeds) a most stringent (i.e., highest) of the user recognition confidence threshold data. Thereafter, the server may send data indicating a user associated with the user recognition data to all of the content sources.