International Business Machines Corporation

Globalfoundries Inc.

Vibha Singhal Sinha

Jalal U Mahmud

Rama Kalyani T Akkiraju

Anbang Xu

Pritam S Gundecha

Debdoot Mukherjee

Shereen M Oraby

Pankaj Dhoolia

Monika Gupta

Mansurul Bhuiyan

Sabina Tomkins

Senthil Kumar Kumarasamy Mani

Haibin Liu

Senthil K Mani

Liang Gou

Rama K Akkiraju

Biplav Srivastava

Satish Chandra

Anuradha Bhamidipaty

Saurabh Sinha

Bikram Sengupta

Pietro Mazzoleni

Md Mansurul A Bhuiyan

Rohan Raju Padhye

Juhnyoung Lee

Sugata Ghosal

Rakesh Mohan

Karthik Visweswariah

Richard Thomas Goodwin

Rema Ananthanarayanan

Parul Alok Mittal

Aubrey J Rembert

Sweefen Goh

Anca Andreea Ivan

Manisha Dattatraya Bhandar

Vamshi Krishna Thotempudi

Mangala Gowri, Iii

Maharshi H Desai

Kathleen Byrnes

Pierre-Hadrien Arnoux

Mengdi Zhang

Gandhi Sivakumar

Bin Xu

Thomas Guthrie Zimmerman

Yuan-Chi Chang

Diptikalyan Saha

Krishna Kummamuru

Karthik Sankaranarayanan

Raman Harishankar

Deepak S Padmanabhan

David Amid

Ateret Anaby-Tavor

Jerald Thomas Schoudt

Zhe Liu

Dinesh Raghu

Neelamadhav Gantayat

Hernan Badenes

Mangala Gowri Nanda

Xiaotong Liu

Thomas Dean Rosinski

Krishna Nandivada Venkata

Gerhard Sigl

Maria Nichole Schwenger

Vinay Kumar Reddy

Yi Wang

Charbak Chatterjee

Anshu N Jain

Vikram Tankasali

Manas R Kumar Singh

Senthil K K Mani

David C D'Lima

Dennis A Conrad

Richard P Gabriel

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.

Recommending a dialog act using model-based textual analysis

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.

Customer care training with situational feedback generation

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.

Brand personality inference and recommendation system

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.

Synthetic narrowband data generation for narrowband automatic speech recognition systems

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.

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.

Customer care training using chatbots

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.

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.

Communication tone training

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.

Tone optimization for digital content

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.

System and method for recommending products to bridge gaps between desired and actual personal branding

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 participant.

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.

Brand personality comparison engine

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.

Determining an impact of a proposed dialog act using model-based textual analysis

Growing community of inventors

Santa Clara, CA, United States of America

Vibha Singhal Sinha