Abstract: A voice command module is used to execute voice commands in a residential environment that contains a plurality of home devices. The voice command module includes a speech recognition module and command logic. The speech recognition module receives utterances from users and converts the utterances to commands from a vocabulary of predetermined commands, which includes a customization command to define a new wake-up utterance as corresponding to a wake-up command. The command logic executes the commands. When the customization command is received, the command logic changes the voice command module so that it now executes the wake-up command upon detection of the new wake-up utterance.

Abstract: In general, techniques are described for identifying a codebook to be used when compressing spatial components of a sound field. A device comprising one or more processors may be configured to perform the techniques. The one or more processors may be configured to identify a Huffman codebook to use when compressing a spatial component of a plurality of spatial components based on an order of the spatial component relative to remaining ones of the plurality of spatial components, the spatial component generated by performing a vector based synthesis with respect to a plurality of spherical harmonic coefficients.

Abstract: Techniques for parsing and execution of data including multiple information classes are described herein. In some examples, a collection of data may include multiple information classes through which the data may be parsed and analyzed. In some examples, the multiple information classes may include a textual character information class, a visual style information class, and an inferred information class, such as may include data identifiable based on information external to the data collection. A plurality of tokens associated with the data collection may be generated. One or more of the plurality of tokens may be organized into a set of instructions. The set of instructions may be provided to a computer program for execution.

Abstract: A method for selective transmission of audio data to a speech processing server uses detection of an acoustic trigger in the audio data in determining the data to transmit. Detection of the acoustic trigger makes use of an efficient computation approach that reduces the amount of run-time computation required, or equivalently improves accuracy for a given amount of computation, by combining a “time delay” structure in which intermediate results of computations are reused at various time delays, thereby avoiding computation of computing new results, and decomposition of certain transformations to require fewer arithmetic operations without sacrificing significant performance. For a given amount of computation capacity the combination of these two techniques provides improved accuracy as compared to current approaches.

Abstract: A reply information recommendation method and apparatus provides recommended reply information suitable for a context that can be quickly and accurately calculated when a user replies to information. A specific solution is: acquiring information to be replied to received by a user and pre-reply information that is input by the user and corresponding to the information to be replied to; performing segmentation processing on the information to be replied to, to obtain a segmentation processing result; learning a stored text interaction history set of the user to obtain a reply model; obtaining candidate reply information with reference to the segmentation processing result of the information to be replied to and the reply model; and calculating a set of recommended reply information with reference to the candidate reply information and the pre-reply information. The embodiments of present invention are used for reply information recommendation.

Abstract: An apparatus and a method for constructing a multilingual acoustic model, and a computer readable recording medium are provided. The method for constructing a multilingual acoustic model includes dividing an input feature into a common language portion and a distinctive language portion, acquiring a tandem feature by training the divided common language portion and distinctive language portion using a neural network to estimate and remove correlation between phonemes, dividing parameters of an initial acoustic model constructed using the tandem feature into common language parameters and distinctive language parameters, adapting the common language parameters using data of a training language, adapting the distinctive language parameters using data of a target language, and constructing an acoustic model for the target language using the adapted common language parameters and the adapted distinctive language parameters.

Abstract: A method for selective transmission of audio data to a speech processing server uses detection of an acoustic trigger in the audio data in determining the data to transmit. Detection of the acoustic trigger makes use of an efficient computation approach that reduces the amount of run-time computation required, or equivalently improves accuracy for a given amount of computation, by using a neural network to determine an indicator of presence of the acoustic trigger. In some example, the neural network combines a “time delay” structure in which intermediate results of computations are reused at various time delays, thereby avoiding computation of computing new results, and decomposition of certain transformations to require fewer arithmetic operations without sacrificing significant performance.

Abstract: System and method for analyzing audio data are provided. The audio data may be analyzed to identify speech prosody. For example, the audio data may be analyzed to select a portion of the audio data containing speech produced by a first speaker. The audio data may be further analyzed to identify speech prosody of the speech within the selected portion. Feedbacks and reports may be provided based on the identified speech prosody.

Abstract: A method for internationalization of a computer application being designed and developed as cloud application in a platform-as-a-service (PaaS) environment includes disposing a translatable texts table in a data layer of the computer application as a common source of translatable texts for all layers of the computer application. The method further includes disposing a text string translation service in a logic layer of the computer application. to expose the translatable texts table disposed in the data layer to a presentation layer of the computer application.

Abstract: A dialog device comprises a natural language interfacing device (chat interface or a telephonic device), and a natural language output device (the chat interface, a display device, or a speech synthesizer outputting to the telephonic device). A computer stores natural language dialog conducted via the interfacing device and constructs a current utterance word-by-word. Each word is chosen by applying a plurality of language models to a context comprising concatenation of the stored dialog and the current utterance thus far. Each language model outputs a distribution over the words of a vocabulary. A recurrent neural network (RNN) is applied to the distributions to generate a mixture distribution. The next word is chosen using the mixture distribution. The output device outputs the current natural language utterance after it has been constructed by the computer.

Abstract: Systems, networked devices, and methods are disclosed for suggesting a response to an incoming message. In one aspect, a method includes receiving, by a first electronic device for a first user, the incoming message from a second user, determining a present emotional state of the second user based on the incoming message, determining a target state of the second user based on the present emotional state, determining a response to the incoming message based on the target state, and writing data derived from the response to an output device. In some aspects, the method also includes identifying other users having characteristics similar to those of the second user, and selecting the response to the incoming message from responses provided to users having the similar characteristics.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: A gain control system for controlling gain applied to an audio signal includes a power estimator configured to estimate the power of a digital signal derived from the audio signal, a digital gain estimator configured to determine, in dependence on the estimated power, a digital gain which would modify the power of the digital signal so as to reach a target power level, and a gain controller configured to adjust an analog gain applied to the audio signal in dependence on the determined digital gain.

Abstract: A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization.

Abstract: A method includes, through a digital platform, encoding a digital media file related to a message from a publisher with decodable data, generating a modified digital media file therefrom, capturing, through a client application of a mobile device of a client user, the modified digital media file playing on a broadcasting device to generate capture data therefrom, and generating a response action of the client user based on analyzing the capture data. The method also includes associating the response action to the message of the publisher, automatically interpreting, through the client application, the modified digital media file to decode the decodable data therein, enabling initiation of the response action without interrupting an experience of concurrent sensing of media content through the broadcasting device by the client user, and providing a capability to the client user to control data thereof generated through the initiated response action.

Abstract: Apparatuses, methods and storage medium associated with a spoken dialog system are disclosed herein. In embodiments, an apparatus for natural machine conversing with a user may comprise a listening component to detect a keyword that denotes start of a conversation; a dialog engine to converse with the user during the conversation; and a controller to selectively activate or cause to be activated one of the listening component or the dialog component, and to pass control to the activated listening component or the activated dialog engine, based at least in part on a state of the conversation. Other embodiments may be disclosed or claimed.

Abstract: Systems and processes for converting speech-to-text are provided. In one example process, speech input can be received. A sequence of states and arcs of a weighted finite state transducer (WFST) can be traversed. A negating finite state transducer (FST) can be traversed. A virtual FST can be composed using a neural network language model and based on the sequence of states and arcs of the WFST. The one or more virtual states of the virtual FST can be traversed to determine a probability of a candidate word given one or more history candidate words. Text corresponding to the speech input can be determined based on the probability of the candidate word given the one or more history candidate words. An output can be provided based on the text corresponding to the speech input.

Abstract: Aspects of the present disclosure relate to a distributed storytelling framework. A server receives an adjacency list comprising a set of nodes linked together by edges. The server converts the adjacency list to a set of generated storylines, each storyline being represented as a key-value pair. A key represents a first node and a value represents a second node linked to the first node by an edge. The server combines first and second storylines, of the set of generated storylines, to generate an additional storyline in response to a value from a first storyline matching a key from a second storyline. The additional storyline includes a single key and multiple values, and is added to the set of generated storylines. The server repeats combining storylines, of the set of generated storylines, to generate additional storylines. The server provides an output corresponding to at least one of the generated storylines.

Abstract: An electronic device includes a first microphone that receives a sound generated for a specific time period, from the outside, a second microphone, which is disposed at a location spaced apart from the first microphone and which receives the sound, an audio converter comprising audio converting circuitry, and a processor electrically connected with the first microphone, the second microphone, and the audio converter. The processor is configured to convert the sound obtained from the first microphone, into a first signal and to convert the sound obtained from the second microphone, into a second signal, using the audio converter, and to determine the sound, which is generated for the specific time period, as a voice or a noise based on a frequency-related correlation between the first signal and the second signal.

Abstract: A computer system for narrating a table using at least one narration template, wherein the table is extracted from a data source is provided. The computer system may include parsing the extracted table. The computer system may also include performing structural analysis on the parsed extracted table. The computer system may further include selecting at least one structural template based on the structural analysis of the parsed extracted table. Additionally, the computer system may include selecting the at least one narration template based on the at least one selected structural template. The computer system may also include applying the at least one selected narration template to the extracted table. The computer system may further include narrating the extracted table based on the applying of the at least one selected narration template to the extracted table.