Abstract: There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing/executing hybrid input predictive data analysis.

Abstract: An apparatus for providing a processed audio signal representation on the basis of input audio signal representation configured to apply an un-windowing, in order to provide the processed audio signal representation on the basis of the input audio signal representation. The apparatus is configured to adapt the un-windowing in dependence on one or more signal characteristics and/or in dependence on one or more processing parameters used for a provision of the input audio signal representation.

Abstract: A model learning apparatus of the present invention has a question/answer-pair expansion unit and a translation-model learning unit. The question/answer-pair expansion unit generates expansion question/answer pairs by increasing the number of question/answer pairs associated with an index indicating that it sounds more like the character. The translation-model learning unit learns a translation model and a reverse translation model by using the expansion question/answer pairs. A response selecting apparatus of the present invention has a record unit, a document search unit, a score calculation unit, and a ranking unit. The record unit records question/answer pairs and the above described learned translation model. The score calculation unit obtains a translation likelihood which is a numerical value based on the probability of obtaining the answer from the input question and calculates a score of each of a search-result question/answer pair with respect to the input question.

Abstract: The quality of user experience (UX) of an information visualization depends on multiple diverse aspects. These include qualitative, quantitative, and contextual parameters that are unmeasurable and incomparable. Hence, measuring the UX of a visualization is challenging. The disclosure herein relates to a system and method that collects, processes, and analyzes a multiple diverse parameters to measure and profile the UX of a visualization. To accomplish this, the system collects data regarding the usage, effectiveness, and user perception of the visualization. The system creates a quantitative and comparable version of all these parameters to measure holistically the UX of the visualization.

Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.

Abstract: Methods and systems are presented for generating a machine learning model using enhanced gradient boosting techniques. The machine learning model is configured to receive inputs corresponding to a set of features and to produce an output based on the inputs. The machine learning model includes multiple layers, wherein each layer includes multiple models. To generate the machine learning model, multiple models are built and trained in parallel for each layer of the machine learning model. The multiple models use different subsets of features to produce corresponding output values. After a layer in built and trained, a collective error may be determined for the layer based on the output values from the different models in the layer. An additional layer of models may be added to the machine learning model to reduce the collective error of a previous layer.

Abstract: It is possible to achieve high analysis accuracy on the whole irrespective of a coverage ratio of a morpheme dictionary. A morpheme prediction section 38 outputs a morpheme label string as a morphological analysis result of input text by inputting a resultant vector generated for each character by a vector combination section 36 into a series predictor and sequentially performing calculation. At this point, there is used the series predictor which is subjected to learning in advance such that a morpheme label string obtained by inputting a resultant vector in which a character vector and a morpheme information vector are combined and which is generated without being combined with the morpheme information vector with a specific probability into the series predictor and sequentially performing the calculation coincides with a morpheme label string of learning data.

Abstract: Various implementations disclosed herein include devices, systems, and methods for providing domain-specific responses. In various implementations, a device includes a non-transitory memory and a processor coupled with the non-transitory memory. In some implementations, a method includes determining a user interest value indicative of a pharmaceutical article that the user is interested in learning about. In some implementations, the pharmaceutical article is associated with a set of media content items that provide information regarding the pharmaceutical article. In some implementations, the method includes setting a configuration parameter of a virtual agent to a configuration value that is based on the pharmaceutical article indicated by the user interest value.

Abstract: Method and system for determining a conversation system from a multi-conversation system using Artificial Intelligence (AI) is provided. The method includes receiving a user query associated with a domain and creating a hierarchical tree comprising a root node and a child node using a first pre-trained machine learning model. The method further includes traversing the hierarchical tree for a path between root node and one leaf child node to identify a topic hierarchy. The path is associated with a confidence score corresponding to mapping between user query and match data of nodes in the path. The method further includes determining a conversation system from the multi-conversation system for outputting data to answer the user query corresponding to one leaf child node of one path with a highest confidence score.

Abstract: In an embodiment, communication data including an interaction between at least two individuals in an organization is received via at least two communication platforms. Content of the interaction is extracted to produce extracted content. A frequency of interaction and a type of interaction between the at least two individuals is determined based on the extracted content. A map representative of social interaction within the organization is generated. The map includes an indication of the frequency of interaction and the type of interaction between the at least two individuals. A new frequency of the interaction and a new type of interaction for at least a first individual of the at least two individuals with another individual is determined based on the map. A signal representing the new frequency of interaction and the new type of interaction with the other individual in the organization is provided to a compute device.

Abstract: Systems and methods are directed to improving speech signal recognition. A method includes obtaining a spatial audio signal; separating a continuous speech signal and a corresponding directivity flag signal for a sound source direction from the spatial audio signal; and combining the continuous speech signal with the corresponding directivity flag signal for the sound source direction to generate a speech activation detection signal for the sound source direction. Because the speech activation detection signal of the sound source direction is obtained by combining the continuous speech signal with the directivity flag signal of the sound source direction, the speech activation detection signal has directivity, reducing the interference from continuous speech signal in other sound source directions.

Abstract: A system, method, and wireless earpieces for implementing a virtual assistant. A request is received from a user to be implemented by wireless earpieces. A virtual assistant is executed on the wireless earpieces. An action is implemented to fulfill the request utilizing the virtual assistant. The wireless earpieces may be a set of wireless earpieces and the virtual assistant may be implemented independently by the wireless earpieces.

Abstract: Described herein is a system for sentiment detection in audio data. The system processes audio frame level features of input audio data using a machine learning algorithm to classify the input audio data into a particular sentiment category. The machine learning algorithm may be a neural network trained using an encoder-decoder method. The training of the machine learning algorithm may include normalization techniques to avoid potential bias in the training data that may occur when the training data is annotated for a perceived sentiment of the speaker.

Abstract: Systems, devices, and methods discussed herein provide improved autonomous agent applications that are configured to provide explanations in response to user-submitted questions. A user query may be received and a classification (e.g., a general question, a specific question) for the user query may be determined based at least in part on a predefined rule set (or a classification model). A set of decision features (e.g., particular user data) associated with a decision generated by a machine-learning model may be identified. An explanation chain may be identified from a plurality of explanation chains based at least in part on the user query. The explanation chain may describe a logical chain of explanations associated with a decision making process related to the machine-learning model. A response to the user query may be provided based at least in part on the explanation chain and the set of decision features.

Abstract: A sound processing method obtains note data representative of a note; obtains an audio signal to be processed; specifies, in accordance with the note, an expression sample representative of a sound expression to be imparted to the note and an expression period, of the audio signal, to which the sound expression is to be imparted to the note; and specifies, in accordance with the expression sample and the expression period, a processing parameter relating to an expression imparting processing for imparting the sound expression to a portion corresponding to the expression period in the audio signal. The method then generates a processed audio signal by performing the expression imparting processing in accordance with the expression sample, the expression period, and the processing parameter to the audio signal.

Abstract: Splitting a natural language sentence into primitive phrases retaining relations of terms includes receiving a natural language sentence, building a parse tree from the natural language sentence using a natural language parser, and recursively identifying discourse markers in subtrees of the parse tree, starting with the highest ranking discourse marker in the parse tree, thereby separating each of the respective subtrees at the respective discourse marker using a set of predefined rules until a set of basic subtrees remains. The recursive identification includes looking-ahead for identifying long ranging discourse markers before identifying local discourse markers.

Abstract: Techniques for joining a device of a third user to a communication between a device of a first user and a device of a second user are described herein. For instance, two or more users may utilize respective computing devices to engage in a telephone call, a video call, an instant-messaging session, or any other type of communication in which the users communicate with each other audibly and/or visually. In some instances, a first user of the two users may issue a voice command requesting to join a device of a third user to the communication. One or more computing devices may recognize this voice command and may attempt to join a device of a third user to the communication.

Abstract: A method for authoring a conversational bot including: receiving conversation data; receiving seed intent data that comprises seed intents having a seed intent label and sample intent-bearing utterances; using an intent mining algorithm to mine the conversation data to determine new utterances to associate with the seed intent; augmenting the seed intent data to include the mined new utterances associated with the seed intents; and uploading the augmented seed intent data into the conversation bot. The intent mining algorithm may include: identifying intent-bearing utterances; identifying candidate intents; for each of the seed intents, identifying seed intent alternatives from the sample intent-bearing utterances; associating the intent-bearing utterances from the conversation data with the seed intents via determining a degree of semantic similarity between the candidate intents of the intent-bearing utterances and the seed intent alternatives.

Abstract: Systems and methods are described herein for disambiguating a voice search query that contains a command keyword by determining whether the user spoke a quotation from a content item and whether the user mimicked or approximated the way the quotation is spoken in the content item. The voice search query is transcribed into a string, and an audio signature of the voice search query is identified. Metadata of a quotation matching the string is retrieved from a database that includes audio signature information for the string as spoken within the content item. The audio signature of the voice search query is compared with the audio signature information in the metadata to determine whether the audio signature matches the audio signature information in the quotation metadata. If a match is detected, then a search result comprising an identifier of the content item from which the quotation comes is generated.

Abstract: An electronic device for natural language understanding includes at least one memory and at least one processor coupled to the at least one memory. The at least one processor is configured to process an utterance using a trained model. The at least one processor is also configured to replace a first portion of the utterance with a first token, where the first token represents a semantic role of the first portion of the utterance based on a slot vocabulary. The at least one processor is further configured to determine a slot value in the utterance based on the first token. In addition, the at least one processor is configured to perform a task corresponding to the utterance based on the determined slot value.