Ayzenberg Jun 2016 - Mar 2018
Lead Data Scientist and Machine Learning Engineer
Waveai Jun 2016 - Mar 2018
Chief Technology Officer - Co-Founder
Netflix Sep 2013 - Aug 2014
Senior Software Engineer and Machine Learning Specialist
Orbitwerks Sep 2013 - Aug 2014
Data Scientist and Machine Learning Engineer and Consultant
Ptc Feb 2008 - Oct 2009
Software Developer
Education:
University of Waterloo 2009 - 2013
University of Waterloo 1989 - 2007
Masters, Mathematics, Computer Science, Philosophy
University of Waterloo 2000 - 2005
Bachelor of Mathematics, Bachelors, Computer Science
Skills:
Java Algorithms Machine Learning Data Analysis Xml C++ Algorithm Design Cluster Natural Language Processing Data Mining Large Scale Data Analysis Clustering Python Apache Spark
Certifications:
The Data Scientist’s Toolbox R Programming Getting and Cleaning Data Exploratory Data Analysis Reproducible Research Statistical Inference Regression Models Machine Learning W/ Andrew Ng of Stanford Edx Verified Certificate For the Analytics Edge Neural Networks and Deep Learning Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization Entrepreneurship 1: Developing the Opportunity
- Sunnyvale CA, US David Loker - Sunnyvale CA, US Christopher Cassion - Sunnyvale CA, US
International Classification:
G10H 1/36 G10H 1/00 G06N 20/00 G10L 13/02
Abstract:
A method and system may provide for interactive song generation. In one aspect, a computer system may present options for selecting a background track. The computer system may generate suggested lyrics based on parameters entered by the user. User interface elements allow the computer system to receive input of lyrics. As the user inputs lyrics, the computer system may update its suggestions of lyrics based on the previously input lyrics. In addition, the computer system may generate proposed melodies to go with the lyrics and the background track. The user may select from among the melodies created for each portion of lyrics. The computer system may optionally generate a computer-synthesized vocal(s) or capture a vocal track of a human voice singing the song. The background track, lyrics, melodies, and vocals may be combined to produce a complete song without requiring musical training or experience by the user.
Determining Personality Profiles Based On Online Social Speech
A method for determining a personality profile of an online user is disclosed. Social speech content data associated with an online user is stored. A machine learning model is used to determine a first personality profile of the online user based at least in part on the social speech content data associated with the online user. A second personality profile of the online user is determined based on the social speech content data using a scientific personality model encoded in an ontology, wherein the ontology encodes statistical relationships between a plurality of words and a plurality of personality traits based on one or more scientific research studies. An ensemble model is applied to determine a third personality profile of the online user based at least in part on the first personality profile and the second personality profile.
Determining Personality Profiles Based On Online Social Speech
- Pasadena CA, US David Hans Herman - Venice CA, US David Ryan Loker - Sunnyvale CA, US Kai Mildenberger - San Francisco CA, US
International Classification:
G06F 17/27 G06K 9/62 G06F 15/18 G06N 3/02
Abstract:
A method for determining a personality profile of an online user is disclosed. Social speech content data associated with an online user is stored. A machine learning model is used to determine a first personality profile of the online user based at least in part on the social speech content data associated with the online user. A second personality profile of the online user is determined based on the social speech content data using a scientific personality model encoded in an ontology, wherein the ontology encodes statistical relationships between a plurality of words and a plurality of personality traits based on one or more scientific research studies. An ensemble model is applied to determine a third personality profile of the online user based at least in part on the first personality profile and the second personality profile.
- Wilmington DE, US David Loker - Sunnyvale CA, US Christopher Cassion - Tampa FL, US
International Classification:
G10H 1/00 G06N 99/00 G06N 5/04
Abstract:
The subject disclosure relates to automated songwriting. In some aspects, a process of the disclosed technology can include steps for training a melody prediction model for selecting melodies for lyrics using a corpus of songs, the melody prediction model including modeled melody features and corresponding modeled patterns of lyric features, receiving lyric input of lyrics including a pattern of lyric features from a user, applying the melody prediction model to the lyric input to automatically generate one or more melodies for the lyric input by matching the pattern of lyric features in the lyric input to a first subset of the modeled melody features using the corresponding modeled patterns of lyric features of the modeled melody features, and providing the one or more melodies to the user to generate a song using the lyrics.
David Loker (1977-1977), Heidi McMinn (1982-1986), Jennifer Conner (1984-1990), Dawn Womack (1979-1983), Jennifer Houston (1972-1979), Valerie Peters (1980-1984)
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