Patents by Inventor Jian Luan
Jian Luan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20210082396Abstract: The present disclosure provides a technical solution of highly empathetic TTS processing, which not only takes a semantic feature and a linguistic feature into consideration, but also assigns a sentence ID to each sentence in a training text to distinguish sentences in the training text. Such sentence IDs may be introduced as training features into a processing of training a machine learning model, so as to enable the machine learning model to learn a changing rule for the changing of acoustic codes of sentences with a context of sentence. A speech naturally changed in rhythm and tone may be output to make TTS more empathetic by performing TTS processing with the trained model. A highly empathetic audio book may be generated using the TTS processing provided herein, and an online system for generating a highly empathetic audio book may be established with the TTS processing as a core technology.Type: ApplicationFiled: May 13, 2019Publication date: March 18, 2021Inventors: Jian LUAN, Shihui LIU
-
Patent number: 10922604Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more instruction sequences. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: training, based at least on training data, a machine learning model to detect one or more predetermined interdependencies amongst a plurality of tokens in the training data; and providing the trained machine learning model to enable classification of one or more instruction sequences. Related methods and articles of manufacture, including computer program products, are also provided.Type: GrantFiled: November 7, 2016Date of Patent: February 16, 2021Assignee: Cylance Inc.Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Eric Petersen, Ming Jin, Ryan Permeh
-
Publication number: 20210043208Abstract: The present disclosure provides method and apparatus for generating a response in a human-machine conversation. A first sound input may be received in the conversation. A first audio attribute may be extracted from the first sound input, wherein the first audio attribute indicates a first condition of a user. A second sound input may be received in the conversation. A second audio attribute may be extracted from the second sound input, wherein the second audio attribute indicates a second condition of a user. A difference between the second audio attribute and the first audio attribute is determined, wherein the difference indicates a condition change of the user from the first condition to the second condition. A response to the second sound input is generated based at least on the condition change.Type: ApplicationFiled: April 19, 2018Publication date: February 11, 2021Inventors: Jian Luan, Zhe Xiao, Xingyu Na, Chi Xiu, Jianzhong JU, Xiang Xu
-
Patent number: 10891928Abstract: In accordance with implementations of the subject matter described herein, there is provided a solution for supporting a machine to automatically generate a song. In this solution, an input from a user is used to determine a creation intention of the user with respect to a song to be generated. Lyrics of the song are generated based on the creation intention. Then, a template for the song is generated based at least in part on the lyrics. The template indicates a melody matching with the lyrics. In this way, it is feasible to automatically create the melody and lyrics which not only conform to the creation intention of the user but also match with each other.Type: GrantFiled: April 18, 2018Date of Patent: January 12, 2021Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Jian Luan, Qinying Liao, Zhen Liu, Nan Yang, Furu Wei
-
Publication number: 20210004649Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first centroids are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first centroids.Type: ApplicationFiled: September 17, 2020Publication date: January 7, 2021Inventors: Jian Luan, Matthew Wolff, Brian Michael Wallace
-
Patent number: 10885401Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more scripts. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one memory. The operations may include: extracting, from an icon associated with a file, one or more features; assigning, based at least on the one or more features, the icon to one of a plurality of clusters; and generating, based at least on the cluster to which the icon is assigned, a classification for the file associated with the icon. Related methods and articles of manufacture, including computer program products, are also provided.Type: GrantFiled: May 31, 2019Date of Patent: January 5, 2021Assignee: Cylance Inc.Inventors: Matthew Wolff, Pedro Silva do Nascimento Neto, Xuan Zhao, John Brock, Jian Luan
-
Patent number: 10810470Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first centroids are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first centroids.Type: GrantFiled: August 7, 2019Date of Patent: October 20, 2020Assignee: Cylance Inc.Inventors: Jian Luan, Matthew Wolff, Brian Wallace
-
Publication number: 20200259850Abstract: A system is provided for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.Type: ApplicationFiled: April 28, 2020Publication date: August 13, 2020Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Michael Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Thomas Wojnowicz, Derek A. Soeder, David N. Beveridge, Yaroslav Oliinyk, Ryan Permeh
-
Publication number: 20200204575Abstract: Systems, methods, and articles of manufacture, including computer program products, are provided for classification systems and methods using modeling. In some example embodiments, there is provided a system that includes at least one processor and at least one memory including program code which when executed by the at least one memory provides operations. The operations can include generating a representation of a sequence of sections of a file and/or determining, from a model including conditional probabilities, a probability for each transition between at least two sequential sections in the representation. The operations can further include classifying the file based on the probabilities for each transition.Type: ApplicationFiled: February 28, 2020Publication date: June 25, 2020Inventors: Jian Luan, Derek A. Soeder
-
Patent number: 10652252Abstract: Systems, methods, and articles of manufacture, including computer program products, are provided for classification systems and methods using modeling. In some example embodiments, there is provided a system that includes at least one processor and at least one memory including program code which when executed by the at least one memory provides operations. The operations can include generating a representation of a sequence of sections of a file and/or determining, from a model including conditional probabilities, a probability for each transition between at least two sequential sections in the representation. The operations can further include classifying the file based on the probabilities for each transition.Type: GrantFiled: September 26, 2017Date of Patent: May 12, 2020Assignee: Cylance Inc.Inventors: Jian Luan, Derek Soeder
-
Patent number: 10637874Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.Type: GrantFiled: November 7, 2016Date of Patent: April 28, 2020Assignee: Cylance Inc.Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andrew Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
-
Publication number: 20200058289Abstract: An automatic dubbing method is disclosed. The method comprises: extracting speeches of a voice from an audio portion of a media content (504); obtaining a voice print model for the extracted speeches of the voice (506); processing the extracted speeches by utilizing the voice print model to generate replacement speeches (508); and replacing the extracted speeches of the voice with the generated replacement speeches in the audio portion of the media content (510).Type: ApplicationFiled: November 21, 2016Publication date: February 20, 2020Inventors: Henry GABRYJELSKI, Jian LUAN, Dapeng Li
-
Publication number: 20200057853Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.Type: ApplicationFiled: October 24, 2019Publication date: February 20, 2020Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
-
Publication number: 20200035209Abstract: In accordance with implementations of the subject matter described herein, there is provided a solution for supporting a machine to automatically generate a song. In this solution, an input from a user is used to determine a creation intention of the user with respect to a song to be generated. Lyrics of the song are generated based on the creation intention. Then, a template for the song is generated based at least in part on the lyrics. The template indicates a melody matching with the lyrics. In this way, it is feasible to automatically create the melody and lyrics which not only conform to the creation intention of the user but also match with each other.Type: ApplicationFiled: April 18, 2018Publication date: January 30, 2020Inventors: Jian LUAN, Qinying LIAO, Zhen LIU, Nan YANG, Furu WEI
-
Patent number: 10503901Abstract: In one respect, there is provided a system for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The at least one memory may include program code that provides operations when executed by the at least one processor. The operations may include: training, based on a training data, a machine learning model to enable the machine learning model to determine whether at least one container file includes at least one file rendering the at least one container file malicious; and providing the trained machine learning model to enable the determination of whether the at least one container file includes at least one file rendering the at least one container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.Type: GrantFiled: November 7, 2016Date of Patent: December 10, 2019Assignee: Cylance Inc.Inventors: Xuan Zhao, Matthew Wolff, John Brock, Brian Wallace, Andy Wortman, Jian Luan, Mahdi Azarafrooz, Andrew Davis, Michael Wojnowicz, Derek Soeder, David Beveridge, Yaroslav Oliinyk, Ryan Permeh
-
Publication number: 20190362196Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first centroids are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first centroids.Type: ApplicationFiled: August 7, 2019Publication date: November 28, 2019Inventors: Jian Luan, Matthew Wolff, Brian Wallace
-
Publication number: 20190286952Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more scripts. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one memory. The operations may include: extracting, from an icon associated with a file, one or more features; assigning, based at least on the one or more features, the icon to one of a plurality of clusters; and generating, based at least on the cluster to which the icon is assigned, a classification for the file associated with the icon. Related methods and articles of manufacture, including computer program products, are also provided.Type: ApplicationFiled: May 31, 2019Publication date: September 19, 2019Inventors: Matthew Wolff, Pedro Silva do Nascimento Neto, Xuan Zhao, John Brock, Jian Luan
-
Patent number: 10417530Abstract: Centroids are used for improving machine learning classification and information retrieval. A plurality of files are classified as malicious or not malicious based on a function dividing a coordinate space into at least a first portion and a second portion such that the first portion includes a first subset of the plurality of files classified as malicious. One or more first geometric regions are defined in the first portion that classify files from the first subset as not malicious. A file is determined to be malicious based on whether the file is located within the one or more first geometric regions.Type: GrantFiled: September 29, 2017Date of Patent: September 17, 2019Assignee: Cylance Inc.Inventors: Jian Luan, Matthew Wolff, Brian Wallace
-
Patent number: 10354173Abstract: In one respect, there is provided a system for training a neural network adapted for classifying one or more scripts. The system may include at least one processor and at least one memory. The memory may include program code that provides operations when executed by the at least one memory. The operations may include: extracting, from an icon associated with a file, one or more features; assigning, based at least on the one or more features, the icon to one of a plurality of clusters; and generating, based at least on the cluster to which the icon is assigned, a classification for the file associated with the icon. Related methods and articles of manufacture, including computer program products, are also provided.Type: GrantFiled: November 21, 2016Date of Patent: July 16, 2019Assignee: Cylance Inc.Inventors: Matthew Wolff, Pedro Silva do Nascimento Neto, Xuan Zhao, John Brock, Jian Luan
-
Patent number: 10262651Abstract: Multi-voice font interpolation is provided. A multi-voice font interpolation engine allows the production of computer generated speech with a wide variety of speaker characteristics and/or prosody by interpolating speaker characteristics and prosody from existing fonts. Using prediction models from multiple voice fonts, the multi-voice font interpolation engine predicts values for the parameters that influence speaker characteristics and/or prosody for the phoneme sequence obtained from the text to spoken. For each parameter, additional parameter values are generated by a weighted interpolation from the predicted values. Modifying an existing voice font with the interpolated parameters changes the style and/or emotion of the speech while retaining the base sound qualities of the original voice.Type: GrantFiled: September 9, 2016Date of Patent: April 16, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Jian Luan, Lei He, Max Leung