Abstract: Embodiments are provided that relate to a computer system, a computer program product, and a computer-implemented method for improving performance of a virtual dialog agent system employing an automated virtual dialog agent. Embodiments involve generating ground truth (GT) from a user's knowledge base, and leveraging the GT to evaluate how the virtual dialog agent performs with the GT. The evaluation measures quality of a multi-turn virtual dialog, and generates a remediation plan directed at an algorithmic improvement of the virtual dialog agent.

Abstract: The disclosed technology provides computer-to-wireless-voice integration methods and systems. In some implementations, the methods and systems deliver real-time voice instructions to users of required time-sensitive actions and ensure that such directives are received and a recipient effectively acts on the directives. The systems and methods include receiving a notification of an event from a terminal in a wireless active voice engine (WAVE) system, determining an active voice directive corresponding to the event with a WAVE module, converting the active voice directive into a voice event via a directive converter, and notifying a targeted recipient of the active voice directive corresponding to the event with a communications module. In some implementations, the systems and methods include sending a confirmation event via the receiver to the communications module that the active voice directive was received by the targeted recipient and communicating the active voice directive has been completed.

Abstract: Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Abstract: Methods and systems for processing audio signals containing speech data are disclosed. Biometric data associated with at least one speaker are extracted from an audio input. A correspondence is determined between the extracted biometric data and stored biometric data associated with a consenting user profile, where a consenting user profile is a user profile indicates consent to store biometric data. If no correspondence is determined, the speech data is discarded, optionally after having been processed.

Abstract: Disclosed herein are computer-implement systems and methods for determining whether an electronic document transiting a computer network is safe for viewing and does not contain malicious code, and automatically routing or deleting such electronic document based on such determination, thus providing quick risk decisions relating to the electronic document using an objective, quantitative method. A search algorithm is employed to detect the presence of words or phrases in the subject electronic document that are possible threats to the computer network. Threat updates may be provided through publicly available threat database. A weight is added to the generated score that accounts for the time that the particular vulnerability has been in the subject threat database. Finally, a PNN is used to quickly and objectively classify the subject electronic document for acceptance, quarantine, or denial.

Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.

Abstract: An audio encoder for encoding an audio signal having a lower frequency band and an upper frequency band includes: a detector for detecting a peak spectral region in the upper frequency band of the audio signal; a shaper for shaping the lower frequency band using shaping information for the lower band and for shaping the upper frequency band using at least a portion of the shaping information for the lower band, wherein the shaper is configured to additionally attenuate spectral values in the detected peak spectral region in the upper frequency band; and a quantizer and coder stage for quantizing a shaped lower frequency band and a shaped upper frequency band and for entropy coding quantized spectral values from the shaped lower frequency band and the shaped upper frequency band.

Abstract: Systems and methods are presented herein for providing a user with a notification or with access to live media on an audio/visual user entertainment system based on a user's conditional request for media content. The user may provide the condition of the request by speaking or by entering the condition of the request into an interactive interface. An identification application analyzes the elements of the user's request and generates a question. The application finds a live media stream with identifiers related to the elements and posts the generated question to a live chat forum associated with the live media stream. The application analyzes posts on the forum made by other users to determine if the condition of the user's request is met. When the application determines a post confirms the condition is met, the application generates a notification and provides the user access to the live media stream.

Abstract: The following relates generally to voice assisted healthcare. In some embodiments, a digital assistant receives audio data, and determines an intent from the audio data. The digital assistant may then match the determined intent to a flow of a set of flows, where the set of flows may include at least one of: (i) submitting a prescription, (ii) refilling a prescription, (iii) changing a pickup location, (iv) requesting a status update for a prescription, or (v) initiating a pharmacy chat session. The matched flow of the set of flows may then be executed.

Abstract: A dialog apparatus 100 is an apparatus for responding to a dialog act of a user. The dialog apparatus 100 is provided with: a policy unit 40 configured to set a score to each of response candidates included in a set of response candidates based on the state of a dialog being performed with the user and a policy parameter, and referring to the set scores, to select one of the response candidates as a dialog act of the dialog apparatus 100; and a policy parameter updating unit 60 configured to obtain a reward in the state of the dialog using a reward function that, as the reward, returns an evaluation of a behavior performed in a specific circumstance as a quantitatively represented numeric value, and to update the policy parameter based on the obtained reward.

Abstract: Provided is a method, computer program product, and system for modifying an input command by a virtual assistant. A processor may receive an input command from a user. The processor may determine a contextual environment surrounding a virtual assistant. The processor may detect, based on the contextual environment, sensitive information in the input command. The processor may replace the sensitive information with generic information. The processor may respond to the input command with an output response based, in part, on the generic information.

Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media for summarizing a call. One of the methods includes generating text corresponding to processing audio produced during an interaction between two participants by executing natural language processing logic. The method includes identifying one or more topics by providing the generated text to a machine learning system, the machine learning system trained to identify topics based on text. The method also includes generating a summary of the interaction based on the one or more topics and the text.

Abstract: A response sentence creation device includes an acquisition unit configured to acquire information indicating a situation and trigger information serving as a trigger of start of response sentence creation, a first query creation unit configured to create a first query for deriving the first answer on the basis of the trigger information, a first answer derivation unit configured to derive a first answer to the first query on the basis of the information indicating the situation, a second query creation unit configured to creates a second query for deriving a second answer on the basis of the first answer, a second answer derivation unit configured to derive the second answer to the second query on the basis of the information indicating the situation, and a response sentence creation unit configured to combine the first answer with the second answer to create a response sentence.

Abstract: A method specifically includes, in a human-computer dialog interaction process, when a server performs slot extraction on user discourse, if there is a slot corresponding to which information fails to be extracted and the slot is an optional key slot, the server asks the user a question to determine whether the information corresponding to the slot is necessary. If the information is necessary, the server further extracts the information corresponding to the slot. If the information is unnecessary, the server does not extract the information corresponding to the slot.

Abstract: Approaches for multitask learning as question answering include an input layer for encoding a context and a question, a self-attention based transformer including an encoder and a decoder, a first bi-directional long-term short-term memory (biLSTM) for further encoding an output of the encoder, a long-term short-term memory (LSTM) for generating a context-adjusted hidden state from the output of the decoder and a hidden state, an attention network for generating first attention weights based on an output of the first biLSTM and an output of the LSTM, a vocabulary layer for generating a distribution over a vocabulary, a context layer for generating a distribution over the context, and a switch for generating a weighting between the distributions over the vocabulary and the context, generating a composite distribution based on the weighting, and selecting a word of an answer using the composite distribution.

Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.

Abstract: Disclosed embodiments provide a framework to assist customers in obtaining relevant responses from brands and other users to the intents communicated by these customers. In response to obtaining an intent, an intent messaging service identifies one or more users that can be provided with the intent to solicit responses to the intent. The one or more users are selected based on characteristics of the intent. The intent messaging service evaluates the responses to the intent from the one or more users to identify relevant responses that can be presented to the customer. The intent messaging service provides the relevant responses to the intent to the customer, which can determine which users to interact with to address the intent.

Abstract: An audio signal decoding device includes a non-transitory memory storage stores audio data in a form of a bitstream; and an audio decoder, by which a first spectral coefficient of a first sub-band of a current frame of an audio signal by decoding the bitstream is obtained; a first average quantity of allocated bits per spectral coefficient of the first sub-band is obtained; a first noise filling gain for the first sub-band is obtained when the first average quantity is less than a threshold; a second spectral coefficient is reconstructed according to the first noise filling gain; a frequency domain audio signal is obtained according to the first spectral coefficient and the second spectral coefficient; and a time domain audio signal is generated according to the frequency domain signal.

Abstract: A sound recognition system including time-dependent analog filtered feature extraction and sequencing. An analog front end (AFE) in the system receives input analog signals, such as signals representing an audio input to a microphone. Features in the input signal are extracted, by measuring such attributes as zero crossing events and total energy in filtered versions of the signal with different frequency characteristics at different times during the audio event. In one embodiment, a tunable analog filter is controlled to change its frequency characteristics at different times during the event. In another embodiment, multiple analog filters with different filter characteristics filter the input signal in parallel, and signal features are extracted from each filtered signal; a multiplexer selects the desired features at different times during the event.