Abstract: Natural language policy text is translated into logical access control policy code with a policy composer that receives natural language policy text, an attribute dictionary connected to the policy composer to define attributes and their logical access control policy equivalents. A natural language policy set is connected to the policy composer and includes samples of natural language policy rules and their logical access control policy equivalents. The policy composer uses natural language processing, the attribute dictionary and the natural language policy set to translate the natural language policy text into logical access control code.

Abstract: A system for providing intelligent part of speech processing of complex natural language is disclosed. The system identifies a multiword concept from an input and replaces the multiword concept with a token to be tagged as a desired part of speech. The system passes the modified text including the token to a part-of-speech tagger to tag each word in the text with the appropriate part-of-speech. The system may replace the token with the original text that the token was utilized to replace so that the original intent of the text is evident. The system may analyze the tagged text to generate analyses and interpretations associated with the input. When multiple multiword concepts are identified, the system may evaluate them by computing scores for each of the multiword concepts that may be replaced with tokens, for each of the modified texts including the tokens, or for any interpretations and analyses thereof.

Abstract: Described herein are systems and methods for providing a natural language comprehension system (NLCS) that iteratively performs an alternating search to gather information that may be used to predict the answer to the question. The NLCS first attends to a query glimpse of the question, and then finds one or more corresponding matches by attending to a text glimpse of the text.

Abstract: Disclosed herein are system, method, and computer program product embodiments for recognizing a human emotion in a message. An embodiment operates by receiving a message from a user. The embodiment labels each word of the message with a part of speech (POS) thereby creating a POS set. The embodiment creates a bag of words (BOW) for the message. The embodiment determines an incongruity score for a combination of words in the POS set using a knowledgebase. The embodiment determines a preliminary emotion detection score for an emotion for the message based on the POS set and the BOW. Finally, the embodiment calculates a final emotion detection score for the emotion for the message based on the preliminary emotion detection score and the incongruity score.

Abstract: A method for identifying codemixed text includes receiving codemixed text and segmenting the codemixed text into a plurality of tokens. Each token includes at least one character and is delineated from any adjacent tokens by a space. For each token of the codemixed text, the method also includes extracting features from the token and predicting a probability distribution over possible languages for the token using a language identifier model configured to receive the extracted features from the token as feature inputs. The method also includes assigning a language to each token of the codemixed text by executing a greedy search on the probability distribution over the possible languages predicted for each respective token.

Abstract: The present technology relates to an audio processing apparatus, an audio processing method, and a program which enable to appropriately eliminate a noise. An audio processing apparatus includes a sound collector which collects audio, an audio enhancer which enhances audio to be extracted using an audio signal collected by the sound collector, an audio attenuator which attenuates the audio to be extracted using the audio signal collected by the sound collector, a noise environment estimator which estimates a surrounding noise environment, and a post-filtering unit which performs post-filtering processing using an audio-enhanced signal from the audio enhancer and an audio-attenuated signal from the audio attenuator, in which the post-filtering unit sets strength of processing for noise elimination according to the noise environment by the noise environment estimator. The present technology can be applied to an apparatus which performs audio recognition processing, such as a mobile phone.

Abstract: This specification relates to a method for controlling an artificial intelligence system which performs a multilingual processing based on artificial intelligence technology. The method for controlling an artificial intelligence system which performs a multilingual processing includes: receiving voice information through a microphone; determining a language of the voice information, based on a preset reference; selecting a specific voice recognition server from a plurality of voice recognition servers which process different languages, based on a result of the determination; and transmitting the voice information to the selected specific voice recognition server.

Abstract: A system may include a camera configured to obtain an image of a user, at least one processor, and at least one non-transitory computer-readable media communicatively coupled to the at least one processor. The non-transitory computer-readable media configured to store one or more instructions that when executed cause or direct the system to perform operations. The operations may include establish a communication session between the system and a device. The communication session may be configured such that the device provides audio for the system. The operations may further include compare the image to a particular user image associated with the system and select a first method of transcription generation from among two or more methods of transcription generation based on the comparison of the image to the particular user image. The operations may also include present, a transcription of the audio generated using the selected first method of transcription generation.

Abstract: Systems and methods for computer-based escalation detection are disclosed. In embodiments, a method includes: determining an occurrence of an interaction event between a first party and a second party within a recording including audio data; analyzing the audio data; determining, based on the analyzing the audio data, an escalation during the interaction event to generate escalation data; saving the escalation data; partitioning each interaction event into a plurality of sections, wherein a first section represents a start of the interaction event, and another section represents an end of the interaction event; assigning a sentiment score for each of the plurality of sections; and calculating an overall sentiment score for the interaction event by combining the sentiment scores for each of the plurality of sections, wherein the saved escalation data includes the overall sentiment score.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: A system and method for implementing a proficiency-driven feedback and improvement platform is disclosed. A particular embodiment includes: establishing a data connection with a learner; generating a distribution of questions to determine the learner's level of proficiency on a topic, the topic being composed of a set of codes and counter-codes; determining the learner proficient on the topic after the learner has demonstrated proficiency on each code and counter-code within the topic; and distributing questions to the learner on codes and counter-codes within the topic until the learner has demonstrated proficiency on each code and counter-code within the topic. A particular embodiment further includes: providing the learner feedback on work according to a set of criteria; and ensuring that only users who have first demonstrated proficiency on one or more criteria in the set of criteria can give feedback on those criteria.

Abstract: Systems and methods for utilizing a cognitive device are disclosed. A method includes: receiving, by a computer device, a query from a cognitive device; processing, by the computer device, the query to generate a processed query; transmitting, by the computer device, the processed query to a mobile device; receiving, by the computer device, an action query result from the mobile device based on the mobile device receiving the processed query and performing an action query; transmitting, by the computer device, the action query result to the cognitive device based on receiving the action query result.

Abstract: A system can be configured to perform tasks such as converting recorded speech to a sequence of phonemes that represent the speech, converting an input sequence of graphemes into a target sequence of phonemes, translating an input sequence of words in one language into a corresponding sequence of words in another language, or predicting a target sequence of words that follow an input sequence of words in a language (e.g., a language model). In a speech recognizer, the RNN system may be used to convert speech to a target sequence of phonemes in real-time so that a transcription of the speech can be generated and presented to a user, even before the user has completed uttering the entire speech input.

Abstract: The various implementations described herein include methods and systems for determining device leadership among voice interface devices. In one aspect, a method is performed at a first electronic device of a plurality of electronic devices, each having microphones, a speaker, processors, and memory storing programs for execution by the processors. The first device detects a voice input. It determines a device state and a relevance of the voice input. It identifies a subset of electronic devices from the plurality to which the voice input is relevant. In accordance with a determination that the subset includes the first device, the first device determines a first score of a criterion associated with the voice input and receives second scores of the criterion from other devices in the subset. In accordance with a determination that the first score is higher than the second scores, the first device responds to the detected input.

Abstract: A system and method for an integrated, multi-modal, multi-device natural language voice services environment may be provided. In particular, the environment may include a plurality of voice-enabled devices each having intent determination capabilities for processing multi-modal natural language utterances in addition to knowledge of the intent determination capabilities of other devices in the environment. Further, the environment may be arranged in a centralized manner, a distributed peer-to-peer manner, or various combinations thereof. As such, the various devices may cooperate to determine intent of multi-modal natural language utterances, and commands, queries, or other requests may be routed to one or more of the devices best suited to take action in response thereto.

Abstract: Artificial intelligence is introduced into an electronic meeting context to perform various tasks before, during, and/or after electronic meetings. The artificial intelligence may analyze a wide variety of data such as data pertaining to other electronic meetings, data pertaining to organizations and users, and other general information pertaining to any topic. Capability is also provided to create, manage, and enforce meeting rules templates that specify requirements and constraints for various aspects of electronic meetings. Embodiments include improved approaches for translation and transcription using multiple translation/transcription services. Embodiments also include using sensors in conjunction with interactive whiteboard appliances to perform person detection, person identification, attendance tracking, and improved meeting start.

Abstract: Artificial intelligence is introduced into an electronic meeting context to perform various tasks before, during, and/or after electronic meetings. The artificial intelligence may analyze a wide variety of data such as data pertaining to other electronic meetings, data pertaining to organizations and users, and other general information pertaining to any topic. Capability is also provided to create, manage, and enforce meeting rules templates that specify requirements and constraints for various aspects of electronic meetings. Embodiments include improved approaches for translation and transcription using multiple translation/transcription services. Embodiments also include using sensors in conjunction with interactive whiteboard appliances to perform person detection, person identification, attendance tracking, and improved meeting start.

Abstract: A media generating and editing system that generates audio playback in alignment with text that has been automatically transcribed from the audio. A transcript data file that includes a plurality of text words transcribed from audio words included in the audio data is stored. Timing data is paired with the text words indicating locations in the audio data of the corresponding audio words from which the text words are transcribed. The audio data is provided for playback at a user device. The text words are displayed on a display screen at a user device and a visual marker is displayed on the display screen to indicate the text words on the display screen in time alignment with the audio playback of the corresponding audio words at the user device. The text words in the transcript data file are amended in response to inputs from the user device.

Abstract: Systems, methods, and non-transitory computer readable media are configured to receive emoji query text. The emoji query text can be in a first language. One or more emojis that satisfy the query text can be returned. The one or more emojis can include at least one emoji which corresponds to a second language different than the first language. Factor values of one or more factors can be calculated. The calculation can be for each of the one or more emojis. Some or all of the one or more emojis can be provided for presentation. The presentation can be based on a ranking of the one or more emojis.

Abstract: An apparatus for encoding a multi-channel signal having at least two channels is provided. The apparatus includes a time-spectral converter, converting sequences of blocks of sample values of the two channels into a frequency domain representation having sequences of blocks of spectral values for the two channels, a block of sampling values having an associated input sampling rate, a block of spectral values of the sequences of blocks that has spectral values up to a maximum input frequency related to the input sampling rate; a multi-channel processor to obtain a result sequence of blocks of spectral values having information related to the two channels; a spectral domain resampler to obtain a resampled sequence of blocks of spectral values; a spectral-time converter for converting the resampled sequence of blocks into a time domain representation; and a core encoder for encoding the output sequence of blocks to obtain an encoded multi-channel signal.