Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a conversation between a first participant and a second participant; receiving, utilizing the processor, an objective of the first participant for the conversation between the first participant and the second participant, where the objective is separate from the conversation; determining, utilizing the processor, a dialog act to be entered by the first participant that meets the objective, utilizing a model, including scoring a plurality of proposed dialog acts based on an amount that each proposed dialog act will change a probability of the objective being achieved during the conversation, and determining the dialog act to be entered, based on the scoring; and returning, utilizing the processor, the dialog act to the first participant.

Abstract: In an approach for training customer service agents using persona-based chatbots, a processor retrieves customer service interaction information. A processor analyzes, using natural language processing, the customer service interaction information, wherein the analyzing includes preprocessing and aggregating the customer service interaction information. A processor interacts with a user. A processor provides feedback to the user, based on the user's style and performance during training.

Abstract: Mechanisms are provided to implement a brand personality inference engine. The mechanisms receive crowdsource information and extract features associated with a brand from the crowdsource information. The crowdsource information comprises natural language content submitted by a plurality of providers to a crowdsource information source. The mechanisms analyze features associated with the brand in accordance with a brand personality model configured to predict a brand personality for the brand based on the features associated with the brand. The mechanisms generate an inferred brand personality data structure, representing a perceived brand personality of providers providing the crowdsource information, and output an output indicating aspects of the perceived brand personality based on the inferred brand personality data structure.

Abstract: A method for generating synthetic telephony narrowband data for training an automatic speech recognition model by receiving a broadband audio data file and then initiating a telephony call using a pre-configured telephone provider to play the broadband audio data file in the telephony call and to record and store audio data generated by transmission of the broadband audio data file in the telephony call, thereby generating the synthetic telephony narrowband data file from the broadband audio data file.

Abstract: A system and apparatus are provided for generating synthetic telephony narrowband data for training an automatic speech recognition model by receiving a broadband audio data file and then initiating a telephony call using a pre-configured telephone provider to play the broadband audio data file in the telephony call and to record and store audio data generated by transmission of the broadband audio data file in the telephony call, thereby generating the synthetic telephony narrowband data file from the broadband audio data file.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: A system, computer program product, and method are disclosed. In an approach to train customer service agent using chatbots. The method includes training a chatbot for a customer chat simulation based on a customer service conversation data, a task scenario, and a customer persona. The method also includes monitoring an interaction between a customer service agent and the chatbot. The method further includes determining an assessment of the performance of the customer service agent based on the interaction between the customer service agent and the chatbot. The method additionally includes generating feedback for the customer service agent based on the assessment of the performance of the customer service agent.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a conversation between a first participant and a second participant; receiving, utilizing the processor, an objective of the first participant for the conversation between the first participant and the second participant, where the objective is separate from the conversation; determining, utilizing the processor, a dialog act to be entered by the first participant that meets the objective, utilizing a model, including scoring a plurality of proposed dialog acts based on an amount that each proposed dialog act will change a probability of the objective being achieved during the conversation, and determining the dialog act to be entered, based on the scoring; and returning, utilizing the processor, the dialog act to the first participant.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a real-time conversation between a first participant and a second participant; receiving, utilizing the processor, an objective of the first participant for the real-time conversation between the first participant and the second participant; determining, utilizing the processor, a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing a model, including scoring a plurality of proposed dialog acts based on an amount that each proposed dialog act will change a probability of the objective being achieved during a current point in the real-time conversation, and determining the dialog act to be entered, based on the scoring; and returning, utilizing the processor, the dialog act to the first participant.

Abstract: An approach is provided that may obtain communication information regarding a communication between a first entity and a second entity while the communication may be ongoing. The communication may include an utterance. A tone associated with the utterance may be identified and may result in an identified tone. An outcome of the communication may be predicted using a machine learning based prediction module and the identified tone.

Abstract: An approach is provided that provides a tone optimization recommendation. The approach obtains a current tone inferred from digital content and a desired tone inference for a target audience. A tone optimization recommendation to reduce a difference between the current tone and the desired tone is determined using a processor. A memory is modified to save the tone optimization recommendation. The tone optimization recommendation is provided.

Abstract: An approach is provided that may obtain communication information regarding a communication between a first entity and a second entity while the communication may be ongoing. The communication may include an utterance. A tone associated with the utterance may be identified and may result in an identified tone. An outcome of the communication may be predicted using a machine learning based prediction module and the identified tone.

Abstract: A system and apparatus are provided for generating synthetic telephony narrowband data for training an automatic speech recognition model by receiving a broadband audio data file and then initiating a telephony call using a pre-configured telephone provider to play the broadband audio data file in the telephony call and to record and store audio data generated by transmission of the broadband audio data file in the telephony call, thereby generating the synthetic telephony narrowband data file from the broadband audio data file.

Abstract: A method for generating synthetic telephony narrowband data for training an automatic speech recognition model by receiving a broadband audio data file and then initiating a telephony call using a pre-configured telephone provider to play the broadband audio data file in the telephony call and to record and store audio data generated by transmission of the broadband audio data file in the telephony call, thereby generating the synthetic telephony narrowband data file from the broadband audio data file.

Abstract: A method, system and a computer program product are provided for making product recommendations to improve a user's personal brand by using the symbolic meanings and utilities of products and a user's brand perceptions along with users input of a desired personal brand imagery to output a set of products that are optimized to help users bridge the gaps between their desired and actual self-brand, thereby enabling a user to navigate products that shape their personal imagery.

Abstract: A computer-implemented method according to one embodiment includes identifying a plurality of communications each having an associated objective, automatically determining a plurality of dialog acts within the plurality of communications, utilizing a classifier, determining a plurality of features within each of the plurality of communications, training the model, utilizing the plurality of communications and associated objectives, the plurality of dialog acts, and the plurality of features, receiving textual data associated with a real-time conversation between a first participant and a second participant, receiving an objective of the first participant for the real-time conversation between the first participant and the second participant, determining a dialog act to be entered by the first participant at a current point in the real-time conversation that meets the objective, utilizing the model, and determining the dialog act to be entered, based on the scoring, and returning the dialog act to the first pa

Abstract: Mechanisms are provided to implement a brand comparison engine. The mechanisms receive a request to compare brand personalities of a first specified brand and a second specified brand and obtain a first brand personality scale associated with the first specified brand and a second brand personality scale associated with the second specified brand. The mechanisms calculate at least one gap value indicating a difference between at least one personality trait in the first brand personality scale and a corresponding at least one personality trait in the second brand personality scale. The mechanisms also output an output indicating an aspect of the at least one gap based on the calculation.

Abstract: A computer-implemented method according to one embodiment includes receiving, utilizing a processor, textual data associated with a conversation between a first participant and a second participant, receiving, utilizing the processor, an objective of the first participant for the conversation between the first participant and the second participant, receiving, utilizing the processor, a proposed dialog act to be entered in the conversation from the first participant, determining, utilizing the processor, an impact of the proposed dialog act on the objective of the first participant, utilizing a model, and performing, utilizing the processor, one or more actions based on the impact of the proposed dialog act.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a personalized interactive decision support system. A personalized product recommendation module executing within the personalized interactive decision support system correlates at least one customer to a set of consumption preferences using a machine learning model based on a set of traits of the at least one customer to form at least one customer-to-preference correlation. The personalized product recommendation module maps a set of products to the set of consumption preferences using a consumption preferences-to-product attribute mapping data structure based on a set of attributes of the set of products to form a set of product-to-preference correlations.

Abstract: A method, a computer program product, and an information handling system is provided for reducing cost and improving real-time performance for analyzing and representing customer care communication progression based on tone assessments by monitoring communications between a plurality of customers and a plurality of representatives to form a plurality of interaction histories. Analyzing a text form of the plurality of interaction histories according to a Tone Latent Dirichlet Allocation [T-LDA] model to determine a plurality of conversation tones. Mapping the plurality of conversation tones to a plurality of conversation phases and providing a representation of the conversation tones identifying a first customer tone at a first conversation phase and a second customer tone at a second conversation phase.