Abstract: Apparatus and methods for generating an encoded audio bitstream, including by including program loudness metadata and audio data in the bitstream, and optionally also program boundary metadata in at least one segment (e.g., frame) of the bitstream. Other aspects are apparatus and methods for decoding such a bitstream, e.g., including by performing adaptive loudness processing of the audio data of an audio program indicated by the bitstream, or authentication and/or validation of metadata and/or audio data of such an audio program. Another aspect is an audio processing unit (e.g., an encoder, decoder, or post-processor) configured (e.g., programmed) to perform any embodiment of the method or which includes a buffer memory which stores at least one frame of an audio bitstream generated in accordance with any embodiment of the method.

Abstract: An embodiment of the invention has been made to solve a problem that it is impossible to store externally transmitted job information if a printer apparatus is in a hard-off state and it is, therefore, necessary to store the job information in an external apparatus on the transmission side. In the embodiment, a wireless communication unit which can transmit/receive data even if no power is supplied receives job information from an external terminal, and stores it in a non-volatile memory. When an information processing apparatus is supplied with power, and enters a normal activation state, it executes the job stored in the non-volatile memory.

Abstract: Detecting and incorporating formatting characteristics within natural language processing analytics. Source documents are ingested and the markup formatting language is identified by the program. Once identified, the markup language is parsed and examined for formatting characteristics, embedded notes, comments and other metadata. The formatting characteristics of the plain text are extracted, along with the plain text, and converted into a common analysis structure (CAS), or CAS-equivalent structure, which annotates the natural language text together with its respective formatting characteristics. The CAS or CAS-equivalent structures are stored and sent to a natural language processing pipeline for further analysis via complex algorithms and rules. The natural language processing results data are curated to reflect meaningful analysis of the extracted CAS or CAS-equivalent structure.

Abstract: A sound signal processing method and device are provided for separating sounds of the respective sound sources even when sounds are recorded asynchronously by a plurality of devices. Specifically, the present invention comprises the steps of instructing each of the plurality of devices to output a reference signal of a different frequency, receiving each of the reference signals output from the speaker of the plurality of devices according to the instruction, receiving sound signals in which each of the reference signals output from the speaker of the plurality of devices is input into the microphone of the plurality of devices, calculating a time shift amount of each of the devices based on each of the received reference signals output from the speaker and the received sound signals, and separating the plurality of signal signals input into the microphone of the plurality of devices based on the calculated time shift amount.

Abstract: Method for echo control using adaptive polynomial filters in sub-band domain starts with loudspeaker that is configured to be driven by a reference signal outputting a loudspeaker signal. Microphone receives at least one of: a near-end speaker signal, ambient noise signal, or the loudspeaker signal and generates a microphone signal. Adaptive polynomial filters in sub-band domain included in adaptive echo canceller (AEC) are configured to adaptively filter representation of the reference signal in a plurality of channels in a sub-band domain based on a clean signal to generate the echo estimate. Echo suppressor is configured to remove an echo estimate from the microphone signal to generate the clean signal. Other embodiments are described.

Abstract: A method is provided for resampling an audio-frequency signal in an audio-frequency signal encoding or decoding operation. The resampling is carried out by a method of interpolation of an order greater than one. The method is such that the interpolated samples are obtained by calculating a weighted average of possible interpolation values calculated over a plurality of intervals covering the time location of the sample to be interpolated. A resampling device is provided, which implements the method, and also an encoder and decoder including at least one resampling device.

Abstract: A method and system are provided for training word embedding of domain-specific words. The method includes training, by a processor, a first word embedding, using a general domain corpus, on one or more terms inputted by a user. The method further includes retraining, by the processor, the first word embedding, using a specific domain corpus, for a Neuro-Linguistic Programming task, to create a tuned word embedding. The method also includes training, by the processor, a Neural Network for the Neuro-Linguistic Programming task, using the specific domain corpus. The method additionally includes incorporating, by the processor, the trained Neural Network and tuned word embedding into a Neural Network-based Neuro-Linguistic Programming task. The retraining of the first word embedding and the training of the Neural Network are performed together, and the tuned word embedding is accelerated due to a change in a hyper parameter for domain-specific words.

Abstract: A method of processing a signal includes taking a signal recorded by a plurality of signal recorders, applying at least one super-resolution technique to the signal to produce an oscillator peak representation of the signal comprising a plurality of frequency components for a plurality of oscillator peaks, computing at least one Cross Channel Complex Spectral Phase Evolution (XCSPE) attribute for the signal to produce a measure of a spatial evolution of the plurality of oscillator peaks between the signal, identifying a known predicted XCSPE curve (PXC) trace corresponding to the frequency components and at least one XCSPE attribute of the plurality of oscillator peaks and utilizing the identified PXC trace to determine a spatial attribute corresponding to an origin of the signal.

Abstract: This disclosure generally relates to a system, apparatus, and method for achieving an adaptive vehicle state-based hands free noise reduction feature. A noise reduction tool is provided for adaptively applying a noise reduction strategy on a sound input that uses feedback speech quality measures and machine learning to develop future noise reduction strategies, where the noise reduction strategies include analyzing vehicle operational state information and external information that are predicted to contribute to cabin noise and selecting noise reducing pre-filter options based on the analysis.

Abstract: A method of automatic generation of a digital thesaurus, the method comprising: parsing the digital text and determining a first lexical unit and a second lexical unit; for each entry of the first lexical unit: selecting n-number of sequential units adjacent to the first lexical unit; generating a first context parameter for the first lexical unit, the first context parameter comprising an indication of each unit of the n-number of sequential units and a frequency of co-occurrence of each unit with the first lexical unit in the digital text; for each entry of the second lexical: selecting, n-number of sequential units adjacent to the second lexical unit; generating a second context parameter; determining a lexical unit relation parameter for the first lexical unit and the second lexical unit by: an interrelation analysis and an analysis of entry co-occurrence.

Abstract: An information processing apparatus to select a token from a document to describe a field of interest includes an obtaining unit, a determining unit, a clustering unit, and a selecting unit. The obtaining unit obtains a list of tokens output from extractors that received the document as an input. Each output token has an extractor score assigned to by an extractor. The determining unit determines, as a word frequency value, a frequency of each word in the list of tokens, determines a token score for each token in the list of tokens, and determines a distance between each token in the list of tokens. The clustering unit clusters each token in the list of tokens into a plurality of groups. The selecting unit selects a token with a group of the plurality of groups to describe the field of interest in the document.

Abstract: The technology of the present application provides software as a service (SaaS) executing on a server in a cloud or network. The SaaS receives data from a mobile device of a user over the network. The SaaS processes the data and returns the processed data to a client application executing on a client device of the user, which user is the same as the user of the mobile device wherein there is no direct communication link, wireless or wired, between the mobile device and the client device. In one aspect, the technology of the present application provides the mobile device as a smartphone and a microphone application to be executed on the smartphone.

Abstract: A method for maintaining conversational cadence may include determining, by a processor, a conversational cadence associated with a user in a social network. The conversational cadence may be determined based on a plurality of messages previously transmitted by the user. The method may also include detecting, by the processor, a reduction in the conversational cadence of the user. The method may further include providing, by the processor, a set of fill-in messages that create an appearance to another user in the social network that there is no reduction in the conversational cadence.

Abstract: A method and system are provided for processing natural language user queries for commanding a user interface to perform functions. Individual user queries are classified in accordance with the types of functions and a plurality of user queries may be related to define a particular command. To assist with classification, a query type for each user query is determined where the query type is one of a functional query requesting a particular new command to perform a particular type of function, an entity query relating to an entity associated with the particular new command having the particular type of function and a clarification query responding to a clarification question posed to clarify a prior user query having the particular type of function. Functional queries may be processed using a plurality of natural language processing techniques and scores from each technique combined to determine which type of function is commanded.

Abstract: A method for maintaining conversational cadence may include determining, by a processor, a conversational cadence associated with a user in a social network. The conversational cadence may be determined based on a plurality of messages previously transmitted by the user. The method may also include detecting, by the processor, a reduction in the conversational cadence of the user. The method may further include providing, by the processor, a set of fill-in messages that create an appearance to another user in the social network that there is no reduction in the conversational cadence.

Abstract: Techniques for learning front-end speech recognition parameters as part of training a neural network classifier include obtaining an input speech signal, and applying front-end speech recognition parameters to extract features from the input speech signal. The extracted features may be fed through a neural network to obtain an output classification for the input speech signal, and an error measure may be computed for the output classification through comparison of the output classification with a known target classification. Back propagation may be applied to adjust one or more of the front-end parameters as one or more layers of the neural network, based on the error measure.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In one example process, discourse input representing a user request can be received. The process can determine one or more possible device characteristics corresponding to the discourse input. Data structure representing a set of devices of an established location can be retrieved. The process can determine, based on the data structure, one or more candidate devices from the set of devices. The one or more candidate devices can correspond to the discourse input. The process can determine, based on the one or more possible device characteristics and one or more actual device characteristics of the one or more candidate devices, a user intent corresponding to the discourse input. Instructions that cause a device of the one or more candidate devices to perform an action corresponding to the user intent can be provided.

Abstract: Embodiments disclosed herein provide systems, methods, and computer readable media for analyzing a conversation between a plurality of participants. In a particular embodiment, a method provides determining a first speaker from the plurality of participants and determining a second speaker from the plurality of participants. The method further provides determining a first plurality of turns comprising portions of the conversation when the first speaker is speaking and determining a second plurality of turns comprising portions of the conversation when the second speaker is speaking The method also provides determining per-turn statistics for turns of the first and second pluralities of turns and identifying phases of the conversation based on the per-turn statistics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving audio data including an utterance, obtaining context data that indicates one or more expected speech recognition results, determining an expected speech recognition result based on the context data, receiving an intermediate speech recognition result generated by a speech recognition engine, comparing the intermediate speech recognition result to the expected speech recognition result for the audio data based on the context data, determining whether the intermediate speech recognition result corresponds to the expected speech recognition result for the audio data based on the context data, and setting an end of speech condition and providing a final speech recognition result in response to determining the intermediate speech recognition result matches the expected speech recognition result, the final speech recognition result including the one or more expected speech recognition results indicated b

Abstract: Concealing a lost audio frame of a received audio signal by performing a sinusoidal analysis of a part of a previously received or reconstructed audio signal, wherein the sinusoidal analysis involves identifying frequencies of sinusoidal components of the audio signal, applying a sinusoidal model on a segment of the previously received or reconstructed audio signal, wherein said segment is used as a prototype frame in order to create a substitution frame for a lost audio frame, and creating the substitution frame for the lost audio frame by time-evolving sinusoidal components of the prototype frame, up to the time instance of the lost audio frame, in response to the corresponding identified frequencies.