International Business Machines Corporation

Nuance Communications, Inc.

Oipenn, Inc.

Intenrational Business Machines Corporation

Raimo Bakis

David Nahamoo

Ellen Marie Eide

Lazaros Polymenakos

Michael Alan Picheny

Jatin Ganhotra

Chulaka Gunasekara

Wael Mohamed Hamza

Song Feng

Li Zhu

Sunil D Shashidhara

Maria Elena Smith

Mark Edward Epstein

Cheng Wu

John Zakos

Dimitri Kanevsky

Amado Nassiff

Peter J Guasti

Jan Sedivy

Rangachari Anand

Roberto Pieraccini

Ladislav Kunc

Jie Z Zeng

William Stuart Meisel

Francis Fado

Miroslav Novak

Ashima Arora

Ridley M Whitaker

Stephane Herman Maes

Bhuvana Ramabhadran

Ponani S Gopalakrishnan

Abraham P Ittycheriah

Andrew Aaron

Gary Robert Hanson

Edward Adam Epstein

Charles T Rutherfoord

Stephen Graham Lawrence

Leonid Rachevsky

Steven J Friedland

Arthur J Nadas

Jiri Havelka

Liqin Shen

Hari Chittaluru

Andy Aaron

Shuang Zhi Wei

A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A unified contextual graph for use by the conversational system, the unified contextual graph comprising components based on database queries of the conversational system and a user dialog between a user and the conversational system. For each of a set of user utterances produced in a dialog with the conversational system, a semantic meaning representation is determined. The semantic meaning representations are converted to respective sentential concept graphs. The unified contextual graph is updated based on new sentential concept graphs while the dialog with the conversational system progresses.

Semantic representation and realization for conversational systems

Embodiments provide a computer implemented method, in a data processing system including a processor and a memory including instructions which are executed by the processor to cause the processor to train an enhanced chatflow system, the method including: ingesting a corpus of information including at least one user input node corresponding to a user question and at least one variation for each user input node; for each user input node: designating the node as a class; storing the node in a dialog node repository; designating each of the at least one variations as training examples for the designated class; converting the classes and the training examples into feature vector representations; training one or more training classifiers using the one or more feature vector representations of the classes; and training classification objectives using the one or more feature vector representations of the training examples.

System and method for enhanced chatflow application

A system and method performs automated domain concept discovery and clustering using word embeddings by receiving a set of documents for natural language processing for a domain, representing a plurality of entries in the set of documents as continuous vectors in a high dimensional continuous space, applying a clustering algorithm based on a mutual information optimization criterion to form a set of clusters, associating each entry of the plurality of entries with each cluster in the set of clusters through formalizing an evidence based model of each cluster given each entry, calculating a mutual information metric between each entry and each cluster using the evidence based model, and identifying a nominal center of each cluster by maximizing the mutual information.

Domain concept discovery and clustering using word embedding in dialogue design

A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A user input is received in a dialog between a user and the conversational system, the user input in a natural language. A domain trained semantic matcher is used to determine a set of entities and a user intent from the user input. One or more queries is generated to selected ones of a plurality of knowledge sources, the knowledge sources created from domain specific knowledge. The results from the one or more queries are ranked based on domain specific knowledge. A system response is presented in the dialog based on at least a highest ranked result from the plurality of knowledge sources.

Implicit dialog approach operating a conversational access interface to web content

A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A unified semantic representation of conversational content between a user and conversational system is created as a contextual graph of concepts and relations. A set of subgraph components of the semantic contextual graph dynamically identified based on a current dialog activity. The identified set of subgraph components in a user interface as a set of graphical elements representing respective concepts and relations.

A method, apparatus and computer program product for creating a dialog system for web content is described. Knowledge is extracted from a target web application for the dialog system. The knowledge includes an organizational structure of the target web application and domain knowledge pertinent to the target web application. A deep learning process associates the domain knowledge with the organization structure of the target application. A plurality of knowledge sources of different respective types are created from the domain knowledge and the organizational structure. Each of the knowledge sources is used for providing answers to user queries to the dialog system. As part of the invention, a semantic matcher is provided to select among the answers provided by the plurality of knowledge sources for a best answer to a user query.

Implicit dialog approach for creating conversational access to web content

Embodiments provide a computer implemented method of training an enhanced chatflow system, comprising: ingesting a corpus of information comprising at least one user input node corresponding to a user question and at least one expert-designed variation for each user input node; matching one or more user inputs to one or more corresponding dialog nodes using regular expressions and delimiters; ingesting one or more usage logs from a deployed dialog system, each usage log comprising at least one user input node; for each user input node: designating the node as a class; storing the node in a dialog node repository; designating each of the at least one variations as training examples for the designated class; converting the classes and the training examples into feature vector representations; training one or more classifiers and one or more classification objectives using the feature vector representations.

An interactive communication system configured to conduct a call with a caller. The interactive communication system comprises at least one computer hardware processor configured to perform: obtaining a plurality of dialog chunks comprising information provided by the caller to the interactive communication system and information provided by the interactive communication system to the caller; generating, based on the plurality of dialog chunks, a respective plurality of feature sets, each of the plurality of feature sets comprising at least one feature generated using a respective dialog chunk of the plurality of dialog chunks; determining, based on the plurality of feature sets, a respective plurality of dialog chunk scores; determining, based at least in part on the plurality of dialog chunk scores, a likelihood that the caller is dissatisfied with the interactive communication system; and when the likelihood exceeds a threshold, performing a remedial action that alters how the call is handled.

Systems and methods for facilitating communication using an interactive communication system

Aspects described herein provide various approaches to annotating text samples in order to construct natural language grammars. A text sample may be selected for annotation. A set of annotation candidates may be generated based on the text sample. A classifier may be used to score the set of annotation candidates in order to obtain a set of annotation scores. One of the annotation candidates may be selected as a suggested annotation for the text sample based on the set of annotation scores. A grammar rule may be derived based on the suggested annotation, and a grammar may be configured to include the annotation-derived grammar rule.

Automated text annotation for construction of natural language understanding grammars

Systems and methods for speech synthesis and, in particular, text-to-speech systems and methods for converting a text input to a synthetic waveform by processing prosodic and phonetic content of a spoken example of the text input to accurately mimic the input speech style and pronunciation. Systems and methods provide an interface to a TTS system to allow a user to input a text string and a spoken utterance of the text string, extract prosodic parameters from the spoken input, and process the prosodic parameters to derive corresponding markup for the text input to enable a more natural sounding synthesized speech.

Systems and methods for text-to-speech synthesis using spoken example

An embodiment of the invention is a software tool used to convert text, speech synthesis markup language (SSML), and/or extended SSML to synthesized audio. Provisions are provided to create, view, play, and edit the synthesized speech, including editing pitch and duration targets, speaking type, paralinguistic events, and prosody. Prosody can be provided by way of a sample recording. Users can interact with the software tool by way of a graphical user interface (GUI). The software tool can produce synthesized audio file output in many file formats.

System for tuning synthesized speech

An embodiment of the invention is a software tool used to convert text, speech synthesis markup language (SSML), and or extended SSML to synthesized audio. Provisions are provided to create, view, play, and edit the synthesized speech including editing pitch and duration targets, speaking type, paralinguistic events, and prosody. Prosody can be provided by way of a sample recording. Users can interact with the software tool by way of a graphical user interface (GUI). The software tool can produce synthesized audio file output in many file formats.

A method for generating a frequency warping function comprising preparing the training speech of a source and a target speaker; performing frame alignment on the training speech of the speakers; selecting aligned frames from the frame-aligned training speech of the speakers; extracting corresponding sets of formant parameters from the selected aligned frames; and generating a frequency warping function based on the corresponding sets of formant parameters. The step of selecting aligned frames preferably selects a pair of aligned frames in the middle of the same or similar frame-aligned phonemes with the same or similar contexts in the speech of the source speaker and target speaker. The step of generating a frequency warping function preferably uses the various pairs of corresponding formant parameters in the corresponding sets of formant parameters as key positions in a piecewise linear frequency warping function to generate the frequency warping function.

Generating a frequency warping function based on phoneme and context

A driving directions system loads into memory a limited subset of prerecorded, spoken utterances of geographic names from a mass media storage. The subset of spoken utterances may be limited, for example, to the geographic names within a predetermined radius (e.g., a few miles) of the driver's present location. The present location of the driver may be manually entered into the driving directions system by the driver, or automatically determined using a global positioning system ('GPS') receiver. As the vehicle moves from its present location, the driving directions system loads into memory new names from the mass media storage and overwrites, if necessary, those which are now geographically out of range. Based on the current location of the driving, the driving directions system can audibly output geographic names from the run-time memory.

On demand TTS vocabulary for a telematics system

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Briarcliff Manor, NY, United States of America

Raimo Bakis