Abstract: A call reminder functionality is provided by an arrangement that is operable with a network-enabled communication device in which a reminder to return a phone call can be generated in an automated manner upon the occurrence of a call event. When the call event occurs, an option is displayed on a user interface (“UI”) on the device to create a link between the call and the user's schedule application. If the user selects the option, a callback task is added to the user's task list maintained by the schedule application, and a reminder to make the callback is generated and then displayed on the UI at a future time. The reminder includes pertinent call information and also includes a button that enables the user to place the callback through the UI (i.e., a “one-click call back”).

Abstract: Technologies are disclosed for to utilizing a virtual assistant to as a meeting agenda facilitator. The virtual assistant may start the meeting, control the flow of the meeting, introduce agenda items, receive comments, display meeting materials associated with the meeting, generate/keep track of follow-up actions, create a meeting record, and the like. In some examples, virtual assistant accesses a meeting agenda to determine what agenda items are to be discussed, what content is to be presented, as well as summaries of the meeting and the agenda items. The meeting agenda may also include an expected duration of each of the agenda items that may be used to keep the meeting on time. The virtual assistant may also generate follow-up actions to be performed. Still yet, the virtual assistant may create a meeting record that can include information recorded from the meeting and is associated with the agenda items discussed.

Abstract: An electronic apparatus and method for enhancement of audio for users with a hearing impairment in a shared listening environment is provided. The electronic apparatus receives first audio content from a media source and detects a first user with a hearing disability as a wearer of the personal listening device. The electronic apparatus modifies one or more features of the first audio content based on an audio enhancement profile associated with the detected first user. Thereafter, the electronic apparatus generates second audio content based on the modification and shares the generated second audio content with the personal listening device.

Abstract: A virtual assistant system for communicating with customers uses human intelligence to correct any errors in the system AI, while collecting data for machine learning and future improvements for more automation. The system may use a modular design, with separate components for carrying out different system functions and sub-functions, and with frameworks for selecting the component best able to respond to a given customer conversation.

Abstract: According to principles described herein, unsupervised statistical models, semi-supervised data models, and HITL methods are combined to create a text normalization system that is both robust and trainable with a minimum of human intervention.

Abstract: A company may implement automated workflows for convenience of users or to reduce support costs. For example, allowing a user to change an address using an automated workflow may be faster or less expensive than with a human agent. In some instances, a first communications session may be started between a first user and a second user. During the first communications session, one or more communications may be processed to select an intent of the first user and a value of an information item communicated by the first user. An automated workflow may be selected to continue assisting the first user, and the first user may be transferred to a second communications session with the automated workflow. The automated workflow may be initialized with the value of the information item that was provided during the first communications session so that the first user does not need to repeat information.

Abstract: Methods, information handling systems and computer readable media are disclosed for determining a priority score for a pending support request document. According to one embodiment, a method includes receiving current support request information from within a pending support request document and accessing current additional information associated with the pending support request document. The method further includes associating a set of parameter values with the pending support request document, wherein the values within the set of parameter values are based on information within one or both of the current support request information or the current additional information.

Abstract: Using a natural language processing (NLP) engine executing in conjunction with a machine that is engaged in first natural language interaction, an analytics intent comprising an analysis type to be performed on a dataset is extracted from the first natural language interaction. Within the dataset, a subset of the dataset comprising data having above a threshold relevance measure with respect to the analytics intent is identified. From the subset, a knowledge graph modeling a set of relationships between data in the subset is constructed. Using the analytics intent and the knowledge graph, a conversational template is customized, augmenting the conversational template with a set of entities corresponding to the analytics intent. To obtain a result, the subset is analyzed using the knowledge graph. A second natural language interaction is presented via the machine, the presenting comprising transforming by the NLP engine the result to fit the customized conversational template.

Abstract: Embodiments of the disclosure provide systems and methods for processing unstructured texts in a medical record. A disclosed system includes at least one processor configured to determine a plurality of word representations of an unstructured text and tag entities in the unstructured text by performing a named entity recognition task on the plurality of word representations. The at least one processor is further configured to determine position embeddings based on positions of words in the unstructured text relative to positions of the tagged entities and concatenate the plurality of word representations with the position embeddings. The at least one processor is also configured to determine relation labels between pairs of tagged entities by performing a relationship extraction task on the concatenated word representations and position embeddings.

Abstract: A system, method, and computer program product to accurately route a call is disclosed, by providing a resource interface having one or more interface elements mapping a resource to a call based on current calls and predicted calls, determining a dynamic handling profile from a plurality of dynamic handling profiles that include call information which maps to a resource to provide a ruleset for handling one or more types of call requests, identifying a routing rule comprising one or more routing rules of the ruleset based on caller information, receiving an activation of a resource interface element of the resource interface to initiate a call routing request to forward an assigned call to the resource, and controlling the call routing request according to the routing rule of the dynamic handling profile to perform a call function associated with the assigned call.

Abstract: Methods and systems for natural language processing include pretraining a machine learning model that is based on a bidirectional encoder representations from transformers model, using a span selection training data set that associates a masked word with a passage. A natural language processing task is performed using the span selection pretrained machine learning model.

Abstract: A method may include obtaining an indicator that a first device is in a location of a second device and in response to obtaining the indicator, sending a redirect request to a communication service provider of the first device to direct, to the second device, incoming communication requests handled by the communication service provider that are directed to the first device. The method may further include after sending the redirect request and after a communication request to a communication session is directed to the first device, obtaining, at the second device, a communication indication to participate in the communication session. The method may further include directing audio of the communication session to a transcription system and obtaining, at the second device, the transcription of the audio from the transcription system. The method may also include presenting, by the second device, the audio and the transcription.

Abstract: A system for providing integrated contact information with search results, comprising a plurality of contact centers, each comprising at least a plurality of contact agents; a callback cloud, comprising at least a plurality of contact agents; a queue manager, comprising at least a software components operating and stored on a computing device; wherein the contact agents receive and respond to customer interactions; further wherein the queue manager monitors contact agent availability; further wherein the queue manager receives interaction requests; and further wherein the queue manager provides queue information to interaction requestors.

Abstract: A system and method for dynamically providing safe call back numbers to use to respond to an inbound communication, the method comprising parsing message records from a message server, analyzing the message records for untrustworthy phone numbers by comparing content of the message records to a reference data set that is retrieved from a database, the reference data set including genuine and fraud data wherein the genuine and fraud data includes entities and contact information corresponding to the entities, determining untrustworthy phone numbers in the message records from the analysis, and generating remedy actions based on the determination of the untrustworthy phone numbers.

Abstract: A virtual assistant server receives a web request such as a HTTP request with one or more call parameters corresponding to a call redirected from an interactive voice response server. The virtual assistant server inputs the received one or more call parameters to a predictive model, which identifies, based on the one or more call parameters, an intelligent communication mode to route the redirected call to. Subsequently, the virtual assistant server routes the redirected call to the intelligent communication mode.

Abstract: Disclosed is an electronic device which includes an audio processing block for voice recognition in a low-power mode. The electronic device includes a digital microphone that receives a voice signal from a user and converts the received voice signal into a PDM signal, and a DMIC interface circuit. The DMIC interface circuit includes a PDM-PCM converting block that converts the PDM signal into a PCM signal, a maxscale gain tuning block that tunes a maxscale gain of the PCM signal received from the PDM-PCM converting block based on a distance information indicating a physical distance between the user and the electronic device acquired in advance of the converting of the PDM signal, and an anti-aliasing block that performs filtering for acquiring voice data of a target frequency band associated with a PCM signal output from the maxscale gain tuning block.

Abstract: An estimator of direction of arrival (DOA) of speech from a far-field talker to a device in the presence of room reverberation and directional noise includes audio inputs received from multiple microphones and one or more beamformer outputs generated by processing the microphone inputs. A first DOA estimate is obtained by performing generalized cross-correlation between two or more of the microphone inputs. A second DOA estimate is obtained by performing generalized cross-correlation between one of the one or more beamformer outputs and one or more of: the microphone inputs and other of the one or more beamformer outputs. A selector selects the first or second DOA estimate based on an SNR estimate at the microphone inputs and a noise reduction amount estimate at the beamformer outputs. The SNR and noise reduction estimates may be obtained based on the detection of a keyword spoken by a desired talker.

Abstract: In some embodiments, a knowledge graph generation system extracts noun-phrases from sentences of a knowledge corpora and determines the relations between the noun-phrases based on a relation classifier that is configured to predict a relation between a pair of entities without restricting the entities to a set of named entities. The knowledge graph generation system further generates a sub-graph for each of the sentences based on the noun-phrases and the determined relations. Nodes or entities of the sub-graph represent the non-phrases in the sentence and edges represent the relations between the noun-phrases connected by the respective edges. The knowledge graph generation system merges the sub-graphs to generate the knowledge graph for the knowledge corpora.

Abstract: A method, computer program product, and/or computer system protects a question-answer dialog system from being attacked by adversarial statements that incorrectly answer a question. A computing device accesses a plurality of adversarial statements that are capable of making an adversarial attack on a question-answer dialog system, which is trained to provide a correct answer to a specific type of question. The computing device utilizes the plurality of adversarial statements to train a machine learning model for the question-answer dialog system. The computing device then reinforces the trained machine learning model by bootstrapping adversarial policies that identify multiple types of adversarial statements onto the trained machine learning model. The computing device then utilizes the trained and bootstrapped machine learning model to avoid adversarial attacks when responding to questions submitted to the question-answer dialog system.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing a data sample in response to a request for a data sample. In one aspect, a method comprises: receiving a request for a new data sample; until a candidate new data sample is generated that satisfies an acceptance criterion, performing operations comprising: generating a candidate new data sample using a generator neural network; processing the candidate new data sample using a discriminator neural network to generate an imitation score; and determining, from the imitation score, whether the candidate new data sample satisfies the acceptance criterion; and providing the candidate new data sample that satisfies the acceptance criterion in response to the received request.