At&t Intellectual Property I, L.p.

Oath Inc.

Verizon Patent and Licensing Inc.

Nuance Communications, Inc.

Verizon Media Inc.

Amanda Joy Stent

Aasish Kumar Pappu

Srinivas Bangalore

Alistair D Conkie

Horst Juergen Schroeter

Benjamin J Stern

Giuseppe Di Fabbrizio

Jay Gordon Wilpon

Mark Charles Beutnagel

Ilija Zeljkovic

Yashar Mehdad

Sungjin Lee

Kapil Raj Thadani

Dragomir Radkov Radev

Brian M Novack

Ann K Syrdal

Taniya Mishra

Yi Chang

Juan A Garay

Yale Song

Keiko Horiguchi

Ricardo Alberto Baeza-Yates

Jerry Birkes

Jordi Vallmitjana

Alejandro Jaimes

Alton Drake, Ii

Robert J Andres

Achint Oommen Thomas

Gary Toretti

James Whitescarver

Manjana Chandrasekharan

Jeffrey Kuwano

Youssef Billawala

John Ruckart

Narendra Kumar Gupta

Joel Tetreault

Yifan Hu

I Dan Melamed

Nobal Bikram Niraula

Diamantino Antionio Caseiro

Youssef Billawal

Hyuckchul Jung

Xiang Li

Software for a website hosting short-text services creates an index of buckets for locality sensitive hashing (LSH). The software stores the index in an in-memory database of key-value pairs. The software creates, on a mobile device, a cache backed by the in-memory database. The software then uses a short text to create a query embedding. The software map the query embedding to corresponding buckets in the index and determines which of the corresponding buckets are nearest neighbors to the query embedding using a similarity measure. The software displays location types associated with each of the buckets that are nearest neighbors in a view in a graphical user interface (GUI) on the mobile device and receives a user selection as to one of the location types. Then the software displays the entities for the selected location type in a GUI view on the mobile device.

Location-based recommendations using nearest neighbors in a locality sensitive hashing (LSH) index

Disclosed herein are systems, computer-implemented methods, and computer-readable media for dialog modeling. The method includes receiving spoken dialogs annotated to indicate dialog acts and task/subtask information, parsing the spoken dialogs with a hierarchical, parse-based dialog model which operates incrementally from left to right and which only analyzes a preceding dialog context to generate parsed spoken dialogs, and constructing a functional task structure of the parsed spoken dialogs. The method can further either interpret user utterances with the functional task structure of the parsed spoken dialogs or plan system responses to user utterances with the functional task structure of the parsed spoken dialogs. The parse-based dialog model can be a shift-reduce model, a start-complete model, or a connection path model.

System and method for dialog modeling

Systems, methods, and computer-readable storage media for intelligent caching of concatenative speech units for use in speech synthesis. A system configured to practice the method can identify speech units that are required for synthesizing speech. The system can request from a server the text-to-speech unit needed to synthesize the speech. The system can then synthesize speech using text-to-speech units already stored and a received text-to-speech unit from the server.

System and method for distributed voice models across cloud and device for embedded text-to-speech

Disclosed are systems and methods for improving interactions with and between computers in content searching, generating, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic creation of a formatted, readable transcript of multimedia content, which is derived, extracted, determined, or otherwise identified from the multimedia content. The formatted, readable transcript can be utilized to increase accuracy and efficiency in search engine optimization, as well as identification of relevant digital content available for communication to a user.

Computerized system and method for formatted transcription of multimedia content

Software for a website hosting short-text services creates an index of buckets for locality sensitive hashing (LSH). The software stores the index in an in-memory database of key-value pairs. The software creates, on a mobile device, a cache backed by the in-memory database. The software then uses a short text to create a query embedding. The software map the query embedding to corresponding buckets in the index and determines which of the corresponding buckets are nearest neighbors to the query embedding using a similarity measure. The software displays location types associated with each of the buckets that are nearest neighbors in a view in a graphical user interface(GUI) on the mobile device and receives a user selection as to one of the location types. Then the software displays the entities for the selected location type in a GUI view on the mobile device.

The present teaching relates to generating user profiles with semantic knowledge. A first information associated with a user is obtained. One or more entities are identified from the first information. The one or more entities are augmented based on second information to generate a set of augmented entities. The set of augmented entities are clustered into a set of hierarchical clusters. A set of user profiles is generated based on the set of hierarchical clusters so that the user profile is to be used to personalize content recommendation.

Method and system for user profiling for content recommendation

One or more techniques and/or systems are provided for audio verification. An audio signal, comprising a code for user verification, may be identified. A second audio signal is created comprising speech. The audio signal and the second audio signal may be altered to comprise a same or similar volume, pitch, amplitude, and/or speech rate. The audio signal and the second audio signal may be combined to generate a verification audio signal. The verification audio signal may be presented to a user for the user verification. Verification may be performed to determine whether the user has access to content or a service based upon user input, obtained in response to the user verification audio signal, matching the code within the user verification audio signal. In an example, the user verification may comprise verifying that the user is human.

Audio verification

Systems, methods, and apparatuses are disclosed for adaptively generating a summary of web-based content based on an attribute of a mobile communication device having transmitted a request for the web-based content. By adaptively generating the summary based on an attribute of the mobile communication device such as an amount of visual space available or a number of characters permitted in the interface, a display of the web-based content may be controlled on the mobile communication device in a way that was not previously available. This enables control of displaying web-based content that has been adaptively generated to be displayed on limited display screens based on a learned attribute of the mobile communication device requesting the web-based content.

Scalable and effective document summarization framework

A fact machine receives a comment string from a webpage and segments the comments into sub-conversations. The fact machine also identifies entities within comments or draft comments as well as a sentiment and/or attributes associated with the entity. The fact machine then queries a knowledge base for facts relating to the entity, the attributes, and/or the sentiment. The fact machine then provides the facts to a user prior to the user posting a draft comment.

Fact machine for user generated content

Disclosed herein is an automated approach for summarizing media content using descriptive information associated with the media content. For example and without limitation, the descriptive information may comprise a title associated with the media content. One or more segments of the media content may be identified to form a media content summary based on each segment's respective similarity to the descriptive information, which respective similarity may be determined using a media content and auxiliary data feature spaces. A shared dictionary of canonical patterns generated using the media content and auxiliary data feature spaces may be used in determining a media content segment's similarity to the descriptive information.

Topical-based media content summarization system and method

Software on a website serves a user of an online content aggregation service a first article that the user views. The software extracts named entities from the first article using a named-entity recognizer. The named-entity recognizer uses a sequence of word embeddings as inputs to a conditional random field (CRF) tool to assign labels to each of the word embeddings. Each of the word embeddings is associated with a word in the first article and is trained using an entire topical article from a corpus of topical articles as a context for the word. The software then creates rankings for articles ingested by the content aggregation service based at least in part on the named entities and serves the user a second article using the rankings.

Scalable multilingual named-entity recognition

The present teaching relates to facilitating a guided dialog with a user. In one example, an input utterance is obtained from the user. One or more task sets are estimated based on the input utterance. Each of the one or more task sets includes a plurality of tasks estimated to be requested by the user via the input utterance and is associated with a confidence score computed based on statistics with respect to the plurality of tasks in the task set. At least one of the one or more task sets is selected based on their respective confidence scores. A response is generated based on the tasks in the selected at least one task set. The response is provided to the user.

Method and system for facilitating a guided dialog between a user and a conversational agent

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Chatham, NJ, United States of America

Amanda Joy Stent