Abstract: One embodiment provides a method for predicting a next action in a conversation system that includes obtaining, by a processor, information from conversation logs and a conversation design. The processor further creates a dialog graph based on the conversation design. Weights and attributes for edges in the dialog graph are determined based on the information from the conversation logs. An unrecognized user input the conversation system is detected. The unrecognized user input is analyzed and a next action is predicted based on dialog nodes in the dialog graph and historical paths. A guiding conversation response is generated based on the predicted next action.

Abstract: One embodiment provides a method that includes obtaining a default language corpus. A second language corpus is obtained based on a second language preference. A first transcription of an utterance is received using the default language corpus and natural language processing (NLP). At least one problem word in the first transcription is determined based on an associated grammatical relevance to neighboring words in the first transcription. Upon determining that a first probability score is below a first threshold, an acoustic lookup is performed for an audible match for the problem word in the first transcription based on an associated acoustical relevance. Upon determining that a second probability score is below a second threshold, it is determined whether a match for the problem word exists in the secondary language corpus. Upon determining that the match exists in the secondary language corpus, a second transcription for the utterance is provided.

Abstract: A computer-implemented method includes identifying a plurality of protected pieces from a conversation. The computer-implemented method further includes generating one or more confidence scores for each protected piece, wherein a confidence score is a degree of associativity between a protected piece and a type of sensitive information. The computer-implemented method further includes determining that the protected piece is associated with the type of sensitive information. The computer-implemented method further includes determining a type of protection action for each protected piece in the plurality of protected pieces. The computer-implemented method further includes performing the type of protection action for each protected piece in the plurality of protected pieces to form a modified conversation that is devoid of the sensitive information. A corresponding computer system and computer program product are also disclosed.

Abstract: One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.

Abstract: A computer-implemented method includes identifying a plurality of protected pieces from a conversation. The computer-implemented method further includes generating one or more confidence scores for each protected piece, wherein a confidence score is a degree of associativity between a protected piece and a type of sensitive information. The computer-implemented method further includes determining that the protected piece is associated with the type of sensitive information. The computer-implemented method further includes determining a type of protection action for each protected piece in the plurality of protected pieces. The computer-implemented method further includes performing the type of protection action for each protected piece in the plurality of protected pieces to form a modified conversation that is devoid of the sensitive information. A corresponding computer system and computer program product are also disclosed.

Abstract: One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.

Abstract: One embodiment provides a method that includes generating, by a processor, a topic graph by converting information to topic nodes and edges in the topic graph. Bridges from a given topic node are provided to a neighbor node based on a weight assignment. The bridges are converted to an electronic form of communication. The processor orders suggested paths based on a determined distance from at least one other topic node to a topic goal node via an earliest topic node on each suggested path. The determined distance is found by a first search of the topic graph.

Abstract: One embodiment provides a method that includes obtaining information including profile information and current event information. A processor generates a topic graph by converting the information to topic nodes in the topic graph. The processor determines a weight assignment for each topic node based on ratios of sums of weights of edges from topic nodes. Bridges are provided from a given topic node to a neighbor based on the weight assignment.

Abstract: One embodiment provides a method comprising maintaining a multi-dimensional data structure partitioned into cells utilizing a tree data structure (“tree”) comprising intervals for each dimension of a multi-dimensional space. To partition an interval for a node of the tree into multiple subintervals, multiple leaf nodes (“leaves”) are generated, each leaf descending from the node. To merge multiple intervals for multiple nodes of the tree, a parent node (“parent”) and multiple leaves descending from the parent are generated, the parent and the leaves are time constrained, and the leaves are scheduled for a merger. When transient data in cells included in a list that corresponds to a leaf scheduled for merger expires, each cell in the list is converted into a cell for inclusion in a different list corresponding to a parent of the leaf, each leaf of the parent removed, and the parent turned into a leaf.

Abstract: One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.

Abstract: One embodiment provides a method comprising maintaining a multi-dimensional data structure partitioned into cells utilizing a tree data structure (“tree”) comprising intervals for each dimension of a multi-dimensional space. To partition an interval for a node of the tree into multiple subintervals, multiple leaf nodes (“leaves”) are generated, each leaf descending from the node. To merge multiple intervals for multiple nodes of the tree, a parent node (“parent”) and multiple leaves descending from the parent are generated, the parent and the leaves are time constrained, and the leaves are scheduled for a merger. When transient data in cells included in a list that corresponds to a leaf scheduled for merger expires, each cell in the list is converted into a cell for inclusion in a different list corresponding to a parent of the leaf, each leaf of the parent removed, and the parent turned into a leaf.

Abstract: In an aspect of the present disclosure, a method for providing an alternate modality of input for filling a form field in response to a failure of voice recognition is disclosed including prompting the user for information corresponding to a field of a form, generating speech data by capturing a spoken response of the user to the prompt using at least one input device, attempting to convert the speech data to text, determining that the attempted conversion has failed, evaluating the failure using at least one speech rule, selecting, based on the evaluation, an alternate input modality to be used for receiving the information corresponding to the field of the form, receiving the information corresponding to the field of the form from the alternate input modality, and injecting the received information into the field of the form.

Abstract: Technical solutions are described method for analyzing a natural language conversation-generating machine. An example computer implemented method includes determining, from a plurality of adjacency pairs in a conversation, a number of base pairs. The computer implemented method also includes determining, from the plurality of adjacency pairs, a number of expansion pairs. The computer implemented method also includes computing a efficiency score for the conversation by computing a ratio of the number of base pairs and the number of expansion pairs.

Abstract: In an aspect of the present disclosure, a method for providing an alternate modality of input for filling a form field in response to a failure of voice recognition is disclosed including prompting the user for information corresponding to a field of a form, generating speech data by capturing a spoken response of the user to the prompt using at least one input device, attempting to convert the speech data to text, determining that the attempted conversion has failed, evaluating the failure using at least one speech rule, selecting, based on the evaluation, an alternate input modality to be used for receiving the information corresponding to the field of the form, receiving the information corresponding to the field of the form from the alternate input modality, and injecting the received information into the field of the form.

Abstract: A computer-implemented method includes identifying a plurality of protected pieces from a conversation. The computer-implemented method further includes generating one or more confidence scores for each protected piece, wherein a confidence score is a degree of associativity between a protected piece and a type of sensitive information. The computer-implemented method further includes determining that the protected piece is associated with the type of sensitive information. The computer-implemented method further includes determining a type of protection action for each protected piece in the plurality of protected pieces. The computer-implemented method further includes performing the type of protection action for each protected piece in the plurality of protected pieces to form a modified conversation that is devoid of the sensitive information. A corresponding computer system and computer program product are also disclosed.

Abstract: Technical solutions are described for generating structured conversational data. An example method includes receiving an utterance that is part of a conversation and identifying the utterance as part of an adjacency pair. The adjacency pair includes two utterances, each produced by different speakers. The method also includes associating the utterance with a label from a predetermined set of labels based on the identifying of the adjacency pair.

Abstract: Embodiments of the present invention provide an apparatus comprising a body including a cavity for storing one or more packages, and a conveyor belt disposed above a top surface of the body. The belt is shaped to receive one or more packages, and the belt is controllable to rotate a package placed on the belt either from the top surface to the cavity for storage or from the cavity to the top surface for dispatch. A package comprises at least one of a drone and a payload transported by the drone. The apparatus further comprises a landing mechanism for stabilizing a drone landing on the apparatus.

Abstract: One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.

Abstract: One embodiment provides a method comprising maintaining a weather model based on predicted weather conditions for an air traffic control zone. A hash table comprising multiple hash entries is maintained. Each hash entry comprises a timestamped predicted weather condition for a cell in the zone. A flight plan request for a drone is received. The request comprises a planned flight path for the drone. For at least one cell on the planned flight path, same latitude or same longitude cells, whichever is most closely orthogonal to a direction of the planned flight path, are heuristically probed. Weather conditions for the at least one cell are estimated based on predicted weather conditions for the same latitude or same longitude cells. An executable flight plan is generated if the planned flight path is feasible based on the estimated weather conditions; otherwise, a report including an explanation of infeasibility is generated instead.

Abstract: One embodiment provides a method comprising answering one or more incoming phone calls received at one or more pre-specified phone numbers utilizing a bot. The bot is configured to engage in a conversation with a caller initiating an incoming phone call utilizing a voice recording that impersonates a human being. The method further comprises recording each conversation the bot engages in, and classifying each recorded conversation as one of poison data or truthful training data based on content of the recorded conversation and one or more learned detection models for detecting poisoned data.