Canyon IP Holdings, LLC

Nuance Communications, Inc.

Pryon Incorporated

Amazon Technologies, Inc.

Other

International Business Machines Corporation

Igor Roditis Jablokov

Marc White

Victor Roman Jablokov

James Richard Terrell, Ii

Charles Willard Cross, Jr

David Nahamoo

Michael C Hollinger

Hilary A Pike

Daniel M Smith

Scott Edward Paden

David W Wintermute

Michael A Zaitzeff

Soonthorn Ativanichayaphong

Benjamin D Lewis

Vaibhava Goel

Etienne Marcheret

Steven John Rennie

Ellen Eide Kislal

Marie Wenzel Meteer

Victor Roditis Jablokov

John Pruitt

Clifford A Pickover

Gerald Matthew McCobb

Chul Sung

Bryan Dempsey

Carmi Rothberg

Ajinkya Jitendra Zadbuke

Chris Timothy Seltzer

Joseph Allen Pruitt

Gregory Pelton

Ellen Marie Eide

Charles W Cross

Erik Bargh Guffrey

Chui Sung

Dominique O'Donnell

Dominique O'donnell

Clifford J Strohofer, Iii

David B Lewis

Lucas Siler

Grant Culver Fowler

Neil Rohit Mallinar

Charles Willard Cross Jr

Disclosed are methods, systems, devices, apparatus, media, and other implementations that include a method for document processing (particularly for training of a machine learning question answering platform, and for ingestion of documents). The method includes obtaining a question dataset (e.g., either from public or private repositories of questions) comprising one or more source questions for document processing by a machine learning question-and-answer system that provides answer data in response to question data submitted by a user, modifying a source question from the question dataset to generate one or more augmented questions with equivalent semantic meanings as that of the source question, and processing a document with the one or more augmented questions.

Methods and systems for improved document processing and information retrieval

Disclosed are methods, systems, devices, apparatus, media, and other implementations, including a method that includes obtaining a query set (e.g., a universal set of questions), performing a question-and-answer (Q-A) search on one or more documents using the query set to produce answer data responsive to one or more questions included in the query set, with the answer data characterizing concepts associated with the one or more documents, and deriving structured output information for the one or more documents based on the answer data produced in response to performing the Q-A search.

Supervised summarization and structuring of unstructured documents

A question-answering system that receive a natural-language question includes a database to provide a basis for that answer and a structured-query generator that constructs a structured query from the question and uses it to obtain an answer to the question from the database.

Visual structure of documents in question answering

Machine-implemented assistance is provided in interaction among multiple parties. This assistance can include recording of evidence of communication, and in particular to recording of evidence of language-based communication between humans and machines. Further, machine-implemented facilitation of dispute resolution based on the recorded evidence may be provided.

Recording evidence of communication in human-machine interactions

An intelligent document system provides one or more users, who are recipients of documents, with a way to 'interact' with the documents for example for the purpose of understanding the content of the documents, and taking appropriate action in response to receiving the documents. Interacting with one or more documents can include navigating the documents guided by semantic content of the documents, asking questions that are answered based on the content of the documents. In some examples, the documents are 'dynamic' in that users can manipulate data in the document for example for multiple different views or analyses. In some examples, the documents are augmented semantics and ontology that will allow the user to accurately navigate the document and achieve the natural interfacing they desire.

Intelligent document system

Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving a source document, applying one or more pre-processes to the source document to produce contextual information representative of the structure and content of the source document, and transforming the source document, based on the contextual information, to generate a question-and-answer searchable document.

Document pre-processing for question-and-answer searching

Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document, and determining whether one or more pre-determined questions stored in a question-answer cache maintained at the local device matches the query data according to one or more matching criteria. The method further includes obtaining from the question-answer cache, in response to a determination that at least one of the pre-determined questions matches the query data received from the remote device, at least one answer data item, associated with at least one pre-determined question, corresponding to an answer to the question relating to the source content.

Systems and methods for question-and-answer searching using a cache

Distributed cloud-based data storage divides a file for storage into a number of portions that are separately stored with two or more storage service providers. The division and/or transmission of the file may be implemented based on arbitrary criteria, including random selection, an applied storage policy or assignment of a given portion to a corresponding storage service provider as examples. One or more portions of the file may be assembled into an upload file that is transmitted to and received from a storage provider. The portions of the file received from the storage provider may be used to reconstruct the file.

Distributed cloud file storage

One or more computing devices may receive audio data from a first client device. The one or more computing devices may also receive a designation of a second client device from the first client device. The one or more computing devices may transcribe the audio data to text, and may further identify profile information associated with a user of the first client device in the transcribed text. The profile information may be stored to a profile associated with the user of the first client device. The one or more computing devices may also transmit at least one of the audio data or the transcribed text to the second client device.

Methods and systems for dynamically updating web service profile information by parsing transcribed message strings

A method for facilitating the updating of a language model includes receiving, at a client device, via a microphone, an audio message corresponding to speech of a user; communicating the audio message to a first remote server; receiving, that the client device, a result, transcribed at the first remote server using an automatic speech recognition system ('ASR'), from the audio message; receiving, at the client device from the user, an affirmation of the result; storing, at the client device, the result in association with an identifier corresponding to the audio message; and communicating, to a second remote server, the stored result together with the identifier.

Corrective feedback loop for automated speech recognition

A method of providing speech transcription performance indication includes receiving, at a user device data representing text transcribed from an audio stream by an ASR system, and data representing a metric associated with the audio stream; displaying, via the user device, said text; and via the user device, providing, in user-perceptible form, an indicator of said metric. Another method includes displaying, by a user device, text transcribed from an audio stream by an ASR system; and via the user device, providing, in user-perceptible form, an indicator of a level of background noise of the audio stream. Another method includes receiving data representing an audio stream; converting said data representing an audio stream to text via an ASR system; determining a metric associated with the audio stream; transmitting data representing said text to a user device; and transmitting data representing said metric to the user device.

Continuous speech transcription performance indication

Methods, systems, and software for converting the audio input of a user of a handheld client device or mobile phone into a textual representation by means of a backend server accessed by the device through a communications network. The text is then inserted into or used by an application of the client device to send a text message, instant message, email, or to insert a request into a web-based application or service. In one embodiment, the method includes the steps of initializing or launching the application on the device; recording and transmitting the recorded audio message from the client device to the backend server through a client-server communication protocol; converting the transmitted audio message into the textual representation in the backend server; and sending the converted text message back to the client device or forwarding it on to an alternate destination directly from the server.

Hosted voice recognition system for wireless devices

A method for presenting additional content for a word that is part of a message, and that is presented by a mobile communication device, includes the steps of: presenting the message, including emphasizing one or more words for which respective additional content is available for presenting by the mobile communication device; receiving an utterance that includes an emphasized word for which additional content is available for presenting by the mobile communication device; and presenting the additional content for the emphasized word included in the utterance received by the mobile communication device. These steps are performed by the mobile communication device.

Facilitating presentation by mobile device of additional content for a word or phrase upon utterance thereof

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Raleigh, NC, United States of America

Igor Roditis Jablokov