IP Library Granted Patent US 12,738,099
Granted Patent B2
US 12,738,099 · App. 18/817,762 · Granted Sep 15, 2026

Personalizing robotic interactions

Inventors: Ron Zass (Kiryat Tivon, IL); Ben Ingel (Binyamina, IL)
G06V40/20G06F40/279G06F40/35G06V40/174G10L13/02G10L15/063G10L15/07G10L15/1807G10L15/22G10L25/51
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Quick Facts
Patent No.
US 12,738,099
App. No.
18/817,762
Granted
Sep 15, 2026
Kind
B2
Abstract

Systems, methods and non-transitory computer readable media for personalizing robotic interactions are provided. For example, a digital data record associated with a relation between a specific digital character and a particular character may be accessed. Further, an input in a natural language may be received from the particular character. Further, a conversational artificial intelligence model may be used to analyze the digital data record and the input to determine a desired movement for a specific portion of a specific body. The specific body may be associated with the specific digital character. Further, digital signals may be generated. The digital signals may be configured to cause the specific portion of the specific body to undergo the desired movement during an interaction of the specific digital character with the particular character.

Claims (91)

1 . A non-transitory computer readable medium storing computer implementable instructions that when executed by at least one processor cause the at least one processor to perform operations for personalizing interactions, the operations comprising:

accessing a first digital data record associated with a relation between a specific digital character and a first character;

receiving from the first character a first input in a natural language;

using a conversational artificial intelligence model to analyze the first digital data record and the first input to determine a first desired movement for a first portion of a specific body, the specific body is associated with the specific digital character, the first desired movement serves a first goal of the specific digital character;

generating first digital signals, the first digital signals are configured to cause the first portion of the specific body to undergo the first desired movement during an interaction of the specific digital character with the first character;

accessing a second digital data record associated with a relation between the specific digital character and a second character, the second character differs from the first character;

receiving from the second character a second input in the natural language, the second input conveys a substantially same meaning as the first input;

using the conversational artificial intelligence model to analyze the second digital data record and the second input to determine a second desired movement for a second portion of the specific body, the second desired movement differs from the first desired movement, the second desired movement serves a second goal of the specific digital character, the second goal differs from the first goal based on a difference between the second digital data record and the first digital data record; and

generating second digital signals, the second digital signals are configured to cause the second portion of the specific body to undergo the second desired movement during an interaction of the specific digital character with the second character.

2 . The non-transitory computer readable medium of claim 1 , wherein the first desired movement is configured to cause the specific body to perform a hand gesture, and wherein the second desired movement is configured to cause the specific body to perform a head gesture.

3 . The non-transitory computer readable medium of claim 1 , wherein the first desired movement is configured to cause the specific body to produce a first facial expression including a smile, and wherein the second desired movement is configured to cause the specific body to produce a second facial expression not including a smile.

4 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise:

using the conversational artificial intelligence model to analyze the first digital data record and the first input to determine the first portion of the specific body; and

using the conversational artificial intelligence model to analyze the second digital data record and the second input to determine the second portion of the specific body, wherein the second portion differs from the first portion.

5 . The non-transitory computer readable medium of claim 1 , wherein the specific digital character is at least one of a digital clone or a digital agent of a specific human individual, the first digital data record is associated with a relation between the specific human individual and the first character, and the second digital data record is associated with a relation between the specific human individual and the second character.

6 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise generating audible speech output during the interaction of the specific digital character with the first character, wherein the generated audible speech output includes an articulation of a first part including a particular word and an articulation of a second part including a non-verbal sound, wherein the first desired movement includes a first sub-movement and a second sub-movement, and wherein the first digital signals are configured to cause the first portion of the specific body to undergo the first sub-movement simultaneously with the articulation of the first part, and to cause the first portion of the specific body to undergo the second sub-movement simultaneously with the articulation of the second part.

7 . The non-transitory computer readable medium of claim 1 , wherein the first digital data record is based on an analysis of at least one historic conversation between the specific digital character and the first character, and the second digital data record is based on an analysis of at least one historic conversation between the specific digital character and the second character.

8 . The non-transitory computer readable medium of claim 1 , wherein the first digital data record is indicative of a first type of social relation, the first type of social relation is associated with the relation between the specific digital character and the first character, the second digital data record is indicative of a second type of social relation, the second type of social relation is associated with the relation between the specific digital character and the second character, the second type of social relation differs from the first type of social relation, the determination of the first desired movement is based on the first type of social relation, the determination of the second desired movement is based on the second type of social relation, and the second desired movement differs from the first desired movement based on the second type of social relation being different from the first type of social relation.

9 . The non-transitory computer readable medium of claim 1 , wherein the first digital data record is indicative of a first degree of friendship, the first degree of friendship is associated with the relation between the specific digital character and the first character, the second digital data record is indicative of a second degree of friendship, the second degree of friendship is associated with the relation between the specific digital character and the second character, the second degree of friendship differs from the first degree of friendship, the determination of the first desired movement is based on the first degree of friendship, the determination of the second desired movement is based on the second degree of friendship, and the second desired movement differs from the first desired movement based on the second degree of friendship being different from the first degree of friendship.

10 . The non-transitory computer readable medium of claim 1 , wherein the second desired movement is associated with a different level of formality than the first desired movement based on a type of relation associated with the relation between the specific digital character and the first character being different from a type of relation between the specific digital character and the second character.

11 . The non-transitory computer readable medium of claim 1 , wherein the second desired movement is associated with a different level of empathy than the first desired movement based on a degree of relation associated with the relation between the specific digital character and the first character being different from a degree of relation between the specific digital character and the second character.

12 . The non-transitory computer readable medium of claim 1 , wherein, based on a type of relation associated with the relation between the specific digital character and the first character, the first desired movement is configured to cause a physical contact between the specific body and the first character, and wherein, based on a type of relation associated with the relation between the specific digital character and the second character, the second desired movement is configured not to cause a physical contact between the specific body and the second character.

13 . The non-transitory computer readable medium of claim 1 , wherein the operations further comprise:

analyzing the first digital data record to identify a first mathematical object in a mathematical space;

analyzing the second digital data record to identify a second mathematical object in the mathematical space;

calculating a convolution of a fragment of the first input to obtain a first numerical result value;

calculating a convolution of a fragment of the second input to obtain a second numerical result value;

calculating a function of the first numerical result value and the first mathematical object to obtain a third mathematical object in the mathematical space;

basing the determination of the first desired movement on the third mathematical object;

calculating a function of the second numerical result value and the second mathematical object to obtain a fourth mathematical object in the mathematical space; and

basing the determination of the second desired movement on the fourth mathematical object.

14 . The non-transitory computer readable medium of claim 1 , wherein the second input includes same words as the first input.

15 . The non-transitory computer readable medium of claim 1 , wherein the specific body is a visual depiction of a virtual body of the specific digital character.

16 . The non-transitory computer readable medium of claim 1 , wherein the specific body is a robot associated with the specific digital character.

17 . The non-transitory computer readable medium of claim 1 , wherein the specific body includes one or more actuators, the generated first digital signals are configured to control a first at least part of the one or more actuators to cause the first portion of the specific body to undergo the first desired movement during the interaction of the specific digital character with the first character, and the generated second digital signals are configured to control a second at least part of the one or more actuators to cause the second portion of the specific body to undergo the second desired movement during the interaction of the specific digital character with the second character.

18 . The non-transitory computer readable medium of claim 1 , wherein the first desired movement is configured to cause the specific body to perform a gesture, and wherein the second desired movement is configured to cause the specific body to produce a facial expression.

19 . A non-transitory computer readable medium storing computer implementable instructions that when executed by at least one processor cause the at least one processor to perform operations for personalizing interactions, the operations comprising:

accessing a first digital data record associated with a relation between a specific digital character and a first character;

receiving from the first character a first input in a natural language, the first input is indicative of a desire of the first character for the specific digital character to perform a first manipulation of a particular object;

based on the first digital data record and the first input, determining to perform the first manipulation of the particular object;

analyzing the first digital data record and the first input to determine a first desired movement for a first portion of a specific body, the specific body is associated with the specific digital character, the first desired movement is configured to cause the first manipulation of the particular object;

generating first digital signals, the first digital signals are configured to cause the first portion of the specific body to undergo the first desired movement;

accessing a second digital data record associated with a relation between the specific digital character and a second character, the second character differs from the first character;

receiving from the second character a second input in the natural language, the second input is indicative of a desire of the second character for the specific digital character to perform a second manipulation of the particular object;

and

based on the second digital data record and the second input, determining not to perform the second manipulation of the particular object.

20 . The non-transitory computer readable medium of claim 19 , wherein the operations further comprise:

receiving from the first character a third input in the natural language;

based on the third input from the first character, determining to perform the second manipulation of the particular object; and

generating second digital signals, the second digital signals are configured to cause a second portion of the specific body to undergo a movement configured to cause the second manipulation of the particular object.

21 . The non-transitory computer readable medium of claim 19 , wherein the operations further comprise:

receiving from the second character a third input in the natural language;

based on the second digital data record and the third input, determining to perform the second manipulation of the particular object; and

generating second digital signals, the second digital signals are configured to cause a second portion of the specific body to undergo a movement configured to cause the second manipulation of the particular object.

22 . The non-transitory computer readable medium of claim 19 , wherein the desire of the first character for the specific digital character to perform the first manipulation of the particular object is a desire of the first character for the specific digital character to bring the particular object to the first character, the desire of the second character for the specific digital character to perform the second manipulation of the particular object is a desire of the second character for the specific digital character to bring the particular object to the second character, and the first desired movement is configured to bring the particular object to the first character.

23 . The non-transitory computer readable medium of claim 19 , wherein the desire of the first character for the specific digital character to perform the first manipulation of the particular object is a desire of the first character for the specific digital character to change a state of the particular object to a particular state, the desire of the second character for the specific digital character to perform the second manipulation of the particular object is a desire of the second character for the specific digital character to change the state of the particular object to the particular state, and the first desired movement is configured to change the state of the particular object to the particular state.

24 . The non-transitory computer readable medium of claim 19 , wherein the first desired movement includes a physical contact with a specific object to cause the first manipulation of the particular object, and no physical contact with the particular object.

25 . A system for personalizing interactions, the system comprising:

at least one processing unit configured to perform operations, the operations comprise:

accessing a first digital data record associated with a relation between a specific digital character and a first character;

receiving from the first character a first input in a natural language;

using a conversational artificial intelligence model to analyze the first digital data record and the first input to determine a first desired movement for a first portion of a specific body, the specific body is associated with the specific digital character, the first desired movement serves a first goal of the specific digital character;

generating first digital signals, the first digital signals are configured to cause the first portion of the specific body to undergo the first desired movement during an interaction of the specific digital character with the first character;

accessing a second digital data record associated with a relation between the specific digital character and a second character, the second character differs from the first character;

receiving from the second character a second input in the natural language, the second input conveys a substantially same meaning as the first input;

using the conversational artificial intelligence model to analyze the second digital data record and the second input to determine a second desired movement for a second portion of the specific body, the second desired movement differs from the first desired movement, the second desired movement serves a second goal of the specific digital character, the second goal differs from the first goal based on a difference between the second digital data record and the first digital data record; and

generating second digital signals, the second digital signals are configured to cause the second portion of the specific body to undergo the second desired movement during an interaction of the specific digital character with the second character.

26 . A method for personalizing interactions, the method comprising:

accessing a first digital data record associated with a relation between a specific digital character and a first character;

receiving from the first character a first input in a natural language;

using a conversational artificial intelligence model to analyze the first digital data record and the first input to determine a first desired movement for a first portion of a specific body, the specific body is associated with the specific digital character, the first desired movement serves a first goal of the specific digital character;

generating first digital signals, the first digital signals are configured to cause the first portion of the specific body to undergo the first desired movement during an interaction of the specific digital character with the first character;

accessing a second digital data record associated with a relation between the specific digital character and a second character, the second character differs from the first character;

receiving from the second character a second input in the natural language, the second input conveys a substantially same meaning as the first input;

using the conversational artificial intelligence model to analyze the second digital data record and the second input to determine a second desired movement for a second portion of the specific body, the second desired movement differs from the first desired movement, the second desired movement serves a second goal of the specific digital character, the second goal differs from the first goal based on a difference between the second digital data record and the first digital data record; and

generating second digital signals, the second digital signals are configured to cause the second portion of the specific body to undergo the second desired movement during an interaction of the specific digital character with the second character.

27 . A non-transitory computer readable medium storing computer implementable instructions that when executed by at least one processor cause the at least one processor to perform operations for personalizing interactions, the operations comprising:

accessing a first digital data record associated with a relation between a specific digital character and a first character;

analyzing the first digital data record to identify a first mathematical object in a mathematical space;

receiving from the first character a first input in a natural language;

calculating a convolution of a fragment of the first input to obtain a first numerical result value;

calculating a function of the first numerical result value and the first mathematical object to obtain a third mathematical object in the mathematical space;

based on the third mathematical object, determining a first desired movement for a first portion of a specific body, the specific body is associated with the specific digital character;

generating first digital signals, the first digital signals are configured to cause the first portion of the specific body to undergo the first desired movement during an interaction of the specific digital character with the first character;

accessing a second digital data record associated with a relation between the specific digital character and a second character, the second character differs from the first character;

analyzing the second digital data record to identify a second mathematical object in the mathematical space;

receiving from the second character a second input in the natural language, the second input conveys a substantially same meaning as the first input;

calculating a convolution of a fragment of the second input to obtain a second numerical result value;

calculating a function of the second numerical result value and the second mathematical object to obtain a fourth mathematical object in the mathematical space;

based on the fourth mathematical object, determining a second desired movement for a second portion of the specific body, the second desired movement differs from the first desired movement; and

generating second digital signals, the second digital signals are configured to cause the second portion of the specific body to undergo the second desired movement during an interaction of the specific digital character with the second character.

Continuity (5)
Provisional Application 63685978 · Aug 22, 2024
Provisional Application 63685988 · Aug 22, 2024
Provisional Application 63549534 · Feb 4, 2024
Provisional Application 63535234 · Aug 29, 2023
Related Publication 20250010458A1 · Jan 9, 2025
References Cited (174)
US 4305131A · Best · 1981 [cited by applicant]
US 6077085A · Parry · 2000 [cited by applicant]
US 6778252B2 · Moulton et al. · 2004 [cited by applicant]
US 8140322B2 · Simonsen et al. · 2012 [cited by applicant]
US 9280973B1 · Soyannwo et al. · 2016 [cited by applicant]
US 9747282B1 · Baker et al. · 2017 [cited by applicant]
US 9864933B1 · Cosic · 2018 [cited by applicant]
US 10289076B2 · Kim · 2019 [cited by examiner]
US 10360716B1 · van der Meulen et al. · 2019 [cited by applicant]
US 10423999B1 · Doctor · 2019 [cited by applicant]
US 10433052B2 · Zass et al. · 2019 [cited by applicant]
US 10467792B1 · Roche · 2019 [cited by applicant]
US 10516938B2 · Zass · 2019 [cited by applicant]
US 10607134B1 · Cosic · 2020 [cited by applicant]
US 10827024B1 · Schissel et al. · 2020 [cited by applicant]
US 11024194B1 · Beigman Klebanov · 2021 [cited by applicant]
US 11107141B1 · Nagarajappa · 2021 [cited by examiner]
US 11140459B2 · Ingel · 2021 [cited by applicant]
US 11159597B2 · Ingel · 2021 [cited by applicant]
US 11195542B2 · Zass · 2021 [cited by applicant]
US 11202131B2 · Zass · 2021 [cited by applicant]
US 11232645B1 · Roche · 2022 [cited by examiner]
US 11244385B1 · Fraser · 2022 [cited by applicant]
US 11520079B2 · Zass · 2022 [cited by applicant]
US 11663182B2 · Emma · 2023 [cited by examiner]
US 11837249B2 · Zass · 2023 [cited by applicant]
US 11966688B1 · Ehrlich · 2024 [cited by applicant]
US 12010399B2 · Ingel et al. · 2024 [cited by applicant]
US 20020087317A1 · Lee et al. · 2002 [cited by applicant]
US 20020161578A1 · Saindon et al. · 2002 [cited by applicant]
US 20020161579A1 · Saindon et al. · 2002 [cited by applicant]
US 20040068410A1 · Mohamed et al. · 2004 [cited by applicant]
US 20040172257A1 · Liqin et al. · 2004 [cited by applicant]
US 20040186712A1 · Coles et al. · 2004 [cited by applicant]
US 20050246165A1 · Pettinelli · 2005 [cited by examiner]
US 20050255431A1 · Baker · 2005 [cited by applicant]
US 20050272013A1 · Knight · 2005 [cited by applicant]
US 20060285654A1 · Nesvadba et al. · 2006 [cited by applicant]
US 20070124166A1 · Van Luchene · 2007 [cited by applicant]
US 20070130529A1 · Shrubsole · 2007 [cited by applicant]
US 20070208569A1 · Subramanian et al. · 2007 [cited by applicant]
US 20070220575A1 · Cooper et al. · 2007 [cited by applicant]
US 20080015968A1 · Van Luchene et al. · 2008 [cited by applicant]
US 20080195386A1 · Proidl · 2008 [cited by applicant]
US 20080295130A1 · Worthen · 2008 [cited by applicant]
US 20090037179A1 · Liu et al. · 2009 [cited by applicant]
US 20090175596A1 · Hirai · 2009 [cited by applicant]
US 20100082326A1 · Bangalore · 2010 [cited by applicant]
US 20100100907A1 · Chang · 2010 [cited by applicant]
US 20100238179A1 · Kelly · 2010 [cited by applicant]
US 20110064388A1 · Brown et al. · 2011 [cited by applicant]
US 20110076992A1 · Chou · 2011 [cited by applicant]
US 20120054619A1 · Spooner et al. · 2012 [cited by applicant]
US 20130038737A1 · Yehezkel et al. · 2013 [cited by applicant]
US 20130110513A1 · Jhunja et al. · 2013 [cited by applicant]
US 20130188862A1 · Lievens · 2013 [cited by applicant]
US 20140142918A1 · Dotterer et al. · 2014 [cited by applicant]
US 20140164507A1 · Tesch et al. · 2014 [cited by applicant]
US 20140303958A1 · Lee et al. · 2014 [cited by applicant]
US 20140358518A1 · Wu et al. · 2014 [cited by applicant]
US 20150092007A1 · Koborita et al. · 2015 [cited by applicant]
US 20150314454A1 · Breazeal · 2015 [cited by examiner]
US 20150319518A1 · Wilson · 2015 [cited by applicant]
US 20150356967A1 · Byron et al. · 2015 [cited by applicant]
US 20160005436A1 · Axen et al. · 2016 [cited by applicant]
US 20160021334A1 · Rossano et al. · 2016 [cited by applicant]
US 20160042766A1 · Kummer · 2016 [cited by applicant]
US 20160049146A1 · Chang · 2016 [cited by applicant]
US 20160132578A1 · Allen · 2016 [cited by applicant]
US 20160254795A1 · Ballard · 2016 [cited by applicant]
US 20160328391A1 · Choi · 2016 [cited by applicant]
US 20160365087A1 · Freud · 2016 [cited by applicant]
US 20170004820A1 · Lv et al. · 2017 [cited by applicant]
US 20170011745A1 · Navaratnam · 2017 [cited by examiner]
US 20170075877A1 · Lepeltier · 2017 [cited by applicant]
US 20170076749A1 · Kanevsky · 2017 [cited by applicant]
US 20170206064A1 · Breazeal · 2017 [cited by examiner]
US 20170255616A1 · Yun et al. · 2017 [cited by applicant]
US 20180143809A1 · Zang et al. · 2018 [cited by applicant]
US 20180174577A1 · Jothilingam et al. · 2018 [cited by applicant]
US 20180174595A1 · Dirac et al. · 2018 [cited by applicant]
US 20180240458A1 · Zass · 2018 [cited by applicant]
US 20180253992A1 · Koul et al. · 2018 [cited by applicant]
US 20180260448A1 · Osotio et al. · 2018 [cited by applicant]
US 20180322875A1 · Adachi · 2018 [cited by applicant]
US 20180357215A1 · Austin et al. · 2018 [cited by applicant]
US 20180374461A1 · Serletic · 2018 [cited by applicant]
US 20190065478A1 · Tsujikawa et al. · 2019 [cited by applicant]
US 20190114302A1 · Bequet · 2019 [cited by applicant]
US 20190164533A1 · Lawrenson et al. · 2019 [cited by applicant]
US 20190166176A1 · Jain et al. · 2019 [cited by applicant]
US 20190250891A1 · Kumar et al. · 2019 [cited by applicant]
US 20190317739A1 · Turek et al. · 2019 [cited by applicant]
US 20190354592A1 · Musham et al. · 2019 [cited by applicant]
US 20200005796A1 · Ziv et al. · 2020 [cited by applicant]
US 20200007946A1 · Olkha · 2020 [cited by applicant]
US 20200039080A1 · Oyaizu · 2020 [cited by examiner]
US 20200042601A1 · Doggett · 2020 [cited by applicant]
US 20200043112A1 · Brinkley, II · 2020 [cited by applicant]
US 20200051566A1 · Shin · 2020 [cited by examiner]
US 20200058289A1 · Gabryjelski et al. · 2020 [cited by applicant]
US 20200066304A1 · Chen · 2020 [cited by applicant]
US 20200105245A1 · Gupta · 2020 [cited by applicant]
US 20200111474A1 · Kumar et al. · 2020 [cited by applicant]
US 20200143813A1 · Nakagawa · 2020 [cited by applicant]
US 20200150981A1 · Westberg et al. · 2020 [cited by applicant]
US 20200159862A1 · Kleiner et al. · 2020 [cited by applicant]
US 20200174776A1 · Vinod et al. · 2020 [cited by applicant]
US 20200221176A1 · Hwang et al. · 2020 [cited by applicant]
US 20200285248A1 · Kim · 2020 [cited by examiner]
US 20200296510A1 · Li et al. · 2020 [cited by applicant]
US 20200311120A1 · Zhao et al. · 2020 [cited by applicant]
US 20200382451A1 · Ogawa · 2020 [cited by examiner]
US 20210019373A1 · Freitag · 2021 [cited by applicant]
US 20210042110A1 · Basyrov et al. · 2021 [cited by applicant]
US 20210043208A1 · Luan · 2021 [cited by examiner]
US 20210063363A1 · Kaminski et al. · 2021 [cited by applicant]
US 20210081101A1 · Speare et al. · 2021 [cited by applicant]
US 20210097976A1 · Chicote et al. · 2021 [cited by applicant]
US 20210182468A1 · Co et al. · 2021 [cited by applicant]
US 20210192824A1 · Chen · 2021 [cited by applicant]
US 20210224319A1 · Ingel · 2021 [cited by applicant]
US 20210225365A1 · Sinha et al. · 2021 [cited by applicant]
US 20210232759A1 · Schick et al. · 2021 [cited by applicant]
US 20210264369A1 · Zass · 2021 [cited by applicant]
US 20210271815A1 · Li et al. · 2021 [cited by applicant]
US 20210279822A1 · Bellaish · 2021 [cited by applicant]
US 20210287150A1 · Zass · 2021 [cited by applicant]
US 20210303318A1 · Raghavan · 2021 [cited by applicant]
US 20210397418A1 · Nikumb et al. · 2021 [cited by applicant]
US 20210400101A1 · Ingel · 2021 [cited by applicant]
US 20220070550A1 · Ingel · 2022 [cited by applicant]
US 20220222441A1 · Liu · 2022 [cited by examiner]
US 20220355487A1 · Rose · 2022 [cited by examiner]
US 20220382524A1 · Ansari et al. · 2022 [cited by applicant]
US 20230048149A1 · Zass · 2023 [cited by applicant]
US 20230049015A1 · Zass · 2023 [cited by applicant]
US 20230052442A1 · Zass · 2023 [cited by applicant]
US 20230057835A1 · Zass · 2023 [cited by applicant]
US 20230069088A1 · Zass · 2023 [cited by applicant]
US 20230095089A1 · Kaliyaperumal et al. · 2023 [cited by applicant]
US 20230115185A1 · Huang et al. · 2023 [cited by applicant]
US 20230252224A1 · Tran · 2023 [cited by applicant]
US 20230409298A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20230418459A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20230418571A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20230418572A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20230418632A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20230418633A1 · Ciminelli et al. · 2023 [cited by applicant]
US 20240055014A1 · Zass · 2024 [cited by applicant]
US 20240086051A1 · Ciminelli et al. · 2024 [cited by applicant]
US 20240220521A1 · Ehrlich · 2024 [cited by applicant]
US 20240220712A1 · Zass · 2024 [cited by applicant]
US 20240220714A1 · Ehrlich · 2024 [cited by applicant]
US 20240256583A1 · Zass · 2024 [cited by applicant]
US 20240256767A1 · Zass · 2024 [cited by applicant]
US 20240265191A1 · Zass · 2024 [cited by applicant]
US 20240265197A1 · Zass · 2024 [cited by applicant]
US 20240273305A1 · Zass · 2024 [cited by applicant]
US 20240276072A1 · Ingel et al. · 2024 [cited by applicant]
US 20250010458A1 · Zass · 2025 [cited by examiner]
AU 2019201980A1 · 2019 [cited by examiner]
CN 1419686A · 2003 [cited by examiner]
CN 102422639A · 2012 [cited by applicant]
CN 110097883A · 2019 [cited by examiner]
CN 113256768A · 2021 [cited by examiner]
EP 1928189A1 · 2008 [cited by applicant]
WO 2017088136A1 · 2017 [cited by applicant]
WO WO2017173141A1 · 2017 [cited by examiner]
WO WO2024129101A1 · 2024 [cited by examiner]
CN-110097883-A translation (Year: 2019). [cited by examiner]
CN-113256768-A translation (Year: 2021). [cited by examiner]
CN-1419686-A translation (Year: 2003). [cited by examiner]
K. Nurgaliyev et al.; “Improved Multi-user Interaction in a Smart Environment through a Preference-Based Conflict Resolution Virtual Assistant,” Nov. 23, 2017 International Conference on Intelligent Environments (IE), 2… [cited by applicant]