公开(公告)号：US12062366B2

公开(公告)日：2024-08-13

申请号：US18072954

申请日：2022-12-01

Applicant: Rovi Guides, Inc.

Inventor： Jeffry Copps Robert Jose ,  Ajay Kumar Mishra

IPC: G10L15/18 ,  G06F16/242 ,  G10L15/26

CPC classification number: G10L15/18 ,  G06F16/243 ,  G10L15/26

Abstract: Systems and methods are described herein for interpreting natural language search queries that account for contextual relevance of words of the search query that would ordinarily not be processed, including, for example, processing each word of the query. Each term is associated with a respective part of speech, and a frequency of occurrence of each term in content metadata is determined. A relevance of each term is then determined based on its respective part of speech and frequency. The natural language search query is then interpreted based on the importance or relevance of each term.

公开(公告)号：US20230169960A1

公开(公告)日：2023-06-01

申请号：US18072954

申请日：2022-12-01

Applicant: Rovi Guides, Inc.

Inventor： Jeffry Copps Robert Jose ,  Ajay Kumar Mishra

IPC: G10L15/18 ,  G06F16/242 ,  G10L15/26

CPC classification number: G10L15/18 ,  G06F16/243 ,  G10L15/26

Abstract: Systems and methods are described herein for interpreting natural language search queries that account for contextual relevance of words of the search query that would ordinarily not be processed, including, for example, processing each word of the query. Each term is associated with a respective part of speech, and a frequency of occurrence of each term in content metadata is determined. A relevance of each term is then determined based on its respective part of speech and frequency. The natural language search query is then interpreted based on the importance or relevance of each term.

公开(公告)号：US20220245901A1

公开(公告)日：2022-08-04

申请号：US17572826

申请日：2022-01-11

Applicant: Rovi Guides, Inc.

Inventor： Aashish Goyal ,  Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06T19/00 ,  G06Q30/02 ,  G06N20/00 ,  G06K9/62

Abstract: Insertion of supplemental content into a virtual environment is automated using a machine learning model. The machine learning model is trained to calculate a confidence value that a candidate virtual object fits into a virtual environment based on an input that includes a candidate virtual object, a list of persistent virtual objects, and a list of temporary virtual objects. The machine learning model is trained using the persistent and temporary objects displayed in the current virtual environment until it predicts that a selected virtual object fits into the current virtual environment. The trained machine learning model is then used to select a virtual object comprising supplemental content to be inserted as a new virtual object in the virtual environment.

公开(公告)号：US11250634B1

公开(公告)日：2022-02-15

申请号：US16940982

申请日：2020-07-28

Applicant: Rovi Guides, Inc.

Inventor： Aashish Goyal ,  Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06T19/00 ,  G06Q30/02 ,  G06N20/00 ,  G06K9/62

Abstract: Insertion of supplemental content into a virtual environment is automated using a machine learning model. The machine learning model is trained to calculate a confidence value that a candidate virtual object fits into a virtual environment based on an input that includes a candidate virtual object, a list of persistent virtual objects, and a list of temporary virtual objects. The machine learning model is trained using the persistent and temporary objects displayed in the current virtual environment until it predicts that a selected virtual object fits into the current virtual environment. The trained machine learning model is then used to select a virtual object comprising supplemental content to be inserted as a new virtual object in the virtual environment.

公开(公告)号：US20240249718A1

公开(公告)日：2024-07-25

申请号：US18423556

申请日：2024-01-26

Applicant: Rovi Guides, Inc.

Inventor： Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G10L15/187 ,  G06F16/632 ,  G06F16/68 ,  G06F16/683 ,  G06N5/02 ,  G10L15/18

CPC classification number: G10L15/187 ,  G06F16/632 ,  G06F16/683 ,  G06F16/686 ,  G06N5/02 ,  G10L15/1822

Abstract: Systems and methods are described for modifying a phonetic search index based on a use frequency associated with phonetic representations of text terms included in metadata of a media item. A first phonetic representation of a text term of the metadata, pronounced as a word, may be generated. A second phonetic representation of the text term may be generated by concatenating a phonetic representation of each letter in the text term. A database may be queried to determine use frequencies of the first and second phonetic representations, one of which may be selected based on a comparison of the use frequencies. A phonetic search index may be modified by including an entry for the selected phonetic representation. A voice query related to the media item may be received, and a reply to the voice query may be generated for output by performing a lookup in the modified phonetic search index.

公开(公告)号：US12038954B2

公开(公告)日：2024-07-16

申请号：US17218963

申请日：2021-03-31

Applicant: Rovi Guides, Inc.

Inventor： Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06F16/00 ,  G06F16/31 ,  G06F16/33 ,  G06F16/332 ,  G06N20/00

CPC classification number: G06F16/3322 ,  G06F16/31 ,  G06F16/3329 ,  G06F16/3349 ,  G06N20/00

Abstract: Systems and methods are described to access a set of reattempt query pairs, where each respective pair comprises an initial query and a reattempt of the initial query, and is associated with an indication of whether a reply generated for output based on the respective query pair was acceptable. In response to determining that a second query received after a first query constitutes a reattempt of the first query, a query pair in the set of reattempt query pairs may be identified that matches at least one of the first query and the second query, and is associated with an indication that a reply generated for output based on the query pair was acceptable. A search may be performed based on the identified query pair in the set of reattempt query pairs, and a reply may be generated for output based on the performed search.

公开(公告)号：US11983828B2

公开(公告)日：2024-05-14

申请号：US17572826

申请日：2022-01-11

Applicant: Rovi Guides, Inc.

Inventor： Aashish Goyal ,  Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06T19/00 ,  G06F18/214 ,  G06N20/00 ,  G06Q30/0241 ,  G06Q30/0251

CPC classification number: G06T19/006 ,  G06F18/214 ,  G06N20/00 ,  G06Q30/0271 ,  G06Q30/0277

Abstract: Insertion of supplemental content into a virtual environment is automated using a machine learning model. The machine learning model is trained to calculate a confidence value that a candidate virtual object fits into a virtual environment based on an input that includes a candidate virtual object, a list of persistent virtual objects, and a list of temporary virtual objects. The machine learning model is trained using the persistent and temporary objects displayed in the current virtual environment until it predicts that a selected virtual object fits into the current virtual environment. The trained machine learning model is then used to select a virtual object comprising supplemental content to be inserted as a new virtual object in the virtual environment.

公开(公告)号：US11928440B2

公开(公告)日：2024-03-12

申请号：US17001911

申请日：2020-08-25

Applicant: Rovi Guides, Inc.

Inventor： Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06F40/58 ,  G06F16/2452 ,  G06F40/263 ,  G06F40/47 ,  G06F40/51

CPC classification number: G06F40/58 ,  G06F16/24522 ,  G06F40/263 ,  G06F40/47 ,  G06F40/51

Abstract: Systems and methods for handling multilingual queries are provided. One example method includes receiving, at a computing device, an input, wherein the input comprises a multi-lingual query comprising at least a first source language and a second source language. The multi-lingual query is translated, word for word, into a destination language to produce a monolingual query, with the word order of the multilingual query and the word order of the monolingual query being the same. The monolingual query is processed using natural language processing to map the mono-lingual query to a natural language query in the destination language.

公开(公告)号：US11922931B2

公开(公告)日：2024-03-05

申请号：US17363651

申请日：2021-06-30

Applicant: Rovi Guides, Inc.

Inventor： Ajay Kumar Mishra ,  Jeffry Copps Robert Jose

IPC: G06F17/00 ,  G06F16/632 ,  G06F16/68 ,  G06F16/683 ,  G06N5/02 ,  G10L15/18 ,  G10L15/187

CPC classification number: G10L15/187 ,  G06F16/632 ,  G06F16/683 ,  G06F16/686 ,  G06N5/02 ,  G10L15/1822

Abstract: Systems and methods are described for modifying a phonetic search index based on a use frequency associated with phonetic representations of text terms included in metadata of a media item. A first phonetic representation of a text term of the metadata, pronounced as a word, may be generated. A second phonetic representation of the text term may be generated by concatenating a phonetic representation of each letter in the text term. A database may be queried to determine use frequencies of the first and second phonetic representations, one of which may be selected based on a comparison of the use frequencies. A phonetic search index may be modified by including an entry for the selected phonetic representation. A voice query related to the media item may be received, and a reply to the voice query may be generated for output by performing a lookup in the modified phonetic search index.

公开(公告)号：US11914561B2

公开(公告)日：2024-02-27

申请号：US16807419

申请日：2020-03-03

Applicant: Rovi Guides, Inc.

Inventor： Jeffry Copps Robert Jose ,  Ajay Kumar Mishra

IPC: G06F16/22 ,  G06F16/242 ,  G06F16/2455

CPC classification number: G06F16/2228 ,  G06F16/243 ,  G06F16/2455

Abstract: A frequency of occurrence for each term in a training data set is determined in relation to the entire training data set. A relational data structure is generated that associates each term in the training data with its respective frequency. Any term that has a frequency below a threshold frequency is then added to a list of relevant words. When a natural language search query is received, a plurality of terms in the natural language search query are identified and compared with the list of relevant words. If any term of the natural language search query is included in the relevant words list, that term is identified as a keyword. The natural language search query is then interpreted based on any identified keywords.