Abstract: A method for recommending results to a user from a search query is provided. The method includes receiving, in a search engine, a search query for a media file from a user, identifying a style preference of the user associated with a one or more media file attributes, based on a user-related search history, selecting, from a database, a one or more media files based on the search query and the style preference of the user, determining a style preference score for the one or more media files based on the media file attributes, and recommending to the user a top ranked media file based on the style preference score. A system including a memory storing instructions and one or more processors to execute the instructions to cause the system to perform the above method is also provided.

Abstract: A method for training a generative image model, including defining multiple sensitive categories and protected attributes associated with multiple training images, determining for a particular sensitive category a distribution of a protected attribute within the training images, and based on the distribution, calculating for each training image a corresponding image debiasing weight value associated with the protected attribute. The method further includes generating annotated training data including the training images, and for each training image, (1) the corresponding image debiasing weight value associated with the protected attribute and (2) a corresponding descriptive text caption. The method further includes performing a training process using the annotated training data to train a generative image model resulting in a trained model.

Abstract: An automated music composition and generation system including a system user interface for enabling system users to review and select one or more musical experience descriptors, as well as time and/or space parameters; and an automated music composition and generation engine, operably connected to the system user interface, for receiving, storing and processing musical experience descriptors and time and/or space parameters selected by the system user, so as to automatically compose and generate one or more digital pieces of music in response to the musical experience descriptors and time and/or space parameters selected by the system user. The automated music composition and generation engine includes: a digital piece creation subsystem for creating and delivering the digital piece of music to the system user interface; and a digital audio sample producing subsystem supported by virtual musical instrument libraries.

Abstract: The present invention provides a computerized method and system for detecting modeling content within a model file without rendering the model file, the method and system including loading the model file into a detection engine, the model file including software code therein. In the method and system, the detection engine scans the model file, detecting descriptor terms within software code. The method and system includes generating a description list for the model file based on the plurality of descriptor terms and executing a conversion engine to review the description list relative to a relational database, the conversion engine electronically generating file terms describing the modeling content within the model file based on input from the relational database. Whereby, the method and system generates a content list for the model file based on the file terms, the content list thereby associated with the model file.

Abstract: An automated music composition and generation system including a system user interface for enabling system users to review and select one or more musical experience descriptors, as well as time and/or space parameters; and an automated music composition and generation engine, operably connected to the system user interface, for receiving, storing and processing musical experience descriptors and time and/or space parameters selected by the system user, so as to automatically compose and generate one or more digital pieces of music in response to the musical experience descriptors and time and/or space parameters selected by the system user. Each digital piece of composed and generated music contains a set of musical notes arranged and performed in the digital piece of music. The engine includes: a digital piece creation subsystem and a digital audio sample producing subsystem supported by virtual musical instrument libraries.

Abstract: An automated music composition and generation process within an automated music composition and generation system driven by lyrical musical experience descriptors. The process involves the system user accessing said automated music composition and generation system, employing an automated music composition and generation engine having a system user interface. The system user interface is used to select and provide musical experience descriptors, including lyrics, to the automated music composition and generation engine for processing by said automated music composition and generation engine. The system user initiates the automated music composition and generation engine to compose and generate music based on the musical experience descriptors and lyrics provided.

Abstract: An automated music composition and generation process within an automated music composition and generation system driven by lyrics. The process involves the system user accessing said automated music composition and generation system, employing an automated music composition and generation engine having a system user interface. The system user interface is used to provide lyrics to the automated music composition and generation engine for processing by the automated music composition and generation engine. The system user initiates the automated music composition and generation engine to compose and generate music based on lyrics the provided as input. The lyrics are analyzed for vowel formants to generate pitch events, which are used to support the automated music composition process.

Abstract: Systems, methods, computing platforms, and storage media for providing image recommendations are disclosed. Exemplary implementations may: receive a set of images; access a context segment graph comprising one or more nodes; identify a subset of images related to a node in the context segment graph; receive one or more user responses for the subset of images; generate one or more models based on the user responses; receive one or more candidate images for a creative campaign; determine, using at least one model, a relatedness value and a responsiveness value for at least a portion of the one or more candidate images; and display a listing of the plurality of candidate images, wherein the listing includes, for each candidate image, a confidence score and one or more of the relatedness and responsiveness values in context to the node.

Abstract: The disclosure relates to tools and methods for creating synthetic images with photo-realistic images. The disclosed face generation technology focuses on photo-realistic results by leveraging analysis of a pool of pre-selected images based on a user selection and preferences. The tools and methods as described herein include limiting the pool of pre-selected images by one or more criteria, including, for example, but not limited to gender, age, skin color, expression, etc. The pre-selection of a more curated pool of images allows a user to include a desired set of criteria and specifications that the user would want in a generated synthetic image or images.

Abstract: A method for receiving a first user query from a user for searching an item, forming a first filter based on the first user query, and forming a first filtered item collection is provided. The method includes predicting a new query based on the first user query and a historical query log, forming a second filter for the new query, and applying the second filter to the first filtered item collection to form a second filtered item collection. Further, associating an item score to each of a plurality of items in the first and second filtered item collections, sorting the plurality of items in the first and second filtered item collections according to the item score associated to each of the plurality of items, and providing, to a user display, an item in the plurality of items in the first or second filtered item collections according to a sorting order.

Abstract: An automated music composition and generation system for automatically composing and generating digital pieces of music using an automated music composition and generation engine driven by a set of emotion-type and style-type musical experience descriptors and time and/or space parameters provided by a system user.

Abstract: Methods for composition aware image search refinement using relevance feedback. A method includes receiving, in response to user input, a relevance area within a plurality of image results, wherein the plurality of image results are provided for display on a user interface in response to a first search query using a plurality of spatial anchors in association with respective semantic datasets, and wherein the relevance area is associated with a target semantic dataset. The method also includes determining a mapping from the target semantic dataset to the plurality of spatial anchors, adjusting, based on the mapping, the semantic datasets associated with the plurality of spatial anchors, and providing for display, in the user interface, a plurality of refined image results in response to a second search query using the plurality of spatial anchors in association with the adjusted semantic datasets.

Abstract: A method and system for displaying a dynamic mosaic of media files, the method comprising: receiving media files, determining a fill direction, constructing a layout, determining an edge set from the media files previously placed on the layout, determining a trailing edge, and adjacent edges, constructing a set of closed rectangles an open rectangle from the trailing edge and adjacent edges, providing a first set of frames by iteratively attempting to fill up to one closed rectangle from the set of closed rectangles, providing a second set of frames by filling the open rectangle by placing one searched media file in the open rectangle if no closed rectangle in the set of closed rectangles can be filled, and inserting one of the first set of frames and the second set of frames into a current layout before updating a current edge set based on the inserted frames.

Abstract: An automated music composition and generation system having an automated music composition and generation engine for processing musical experience descriptors and space parameters selected by the system user. The engine includes: a user taste generation subsystem for automatically determining the musical tastes and preferences of each system user based on user feedback and autonomous piece analysis, and maintaining a system user profile reflecting musical tastes and preferences of each system user; and a population taste aggregation subsystem for aggregating the musical tastes and preferences of the population of system users, and modifying the musical experience descriptors and/or time and/or space parameters provided to the automated music composition and generation engine, so that the digital pieces of composed music better reflect the musical tastes and preferences of the population of system users and meet future system user requests for automated music compositions.

Abstract: An automated music composition and generation system having an automated music composition and generation engine for receiving, storing and processing musical experience descriptors and time and/or space parameters selected by the system user. The automated music composition and generation engine includes a user taste generation subsystem for automatically (i) determining the musical tastes and preferences of a system user based on user feedback and autonomous piece analysis, (ii) maintaining a system user profile reflecting musical tastes and preferences of each system user, and (iii) using the musical taste and preference information to change or modify the musical experience descriptors provided to the system to produce a digital piece of composed music composition that better reflects the musical tastes and preferences of the system user.

Abstract: Methods for predicting network access probability of data files accessible over a computer network are provided. In one aspect, a method includes generating a primary data vector for a media file based on a stored data representation of the file, and providing the data vector for the file to an algorithm that uses past interaction information for at least one other media file from a collection of media files having a degree of similarity with the media file above a threshold similarity value. The method also includes receiving, as an output of the algorithm, a marketability score for the media file, the score indicative of a likelihood that a user will download the media file. Systems and machine-readable media are also provided.

Abstract: A method for providing recommendations of creative professionals to complete a project is provided. The method includes receiving information related to a project, the information including a first set of criteria associated with the project. The method includes determining, using a statistical model, a vector representation corresponding to a candidate creative professional based on the information related to the project. The method also includes determining respective vector representations of a first set of creative professionals based at least in part on profile information related to each of the creative professionals. The method includes determining respective distances of each of the respective vector representations from the vector representation corresponding to the candidate creative professional. Further, the method includes providing a second set of creative professionals as recommendations for being assigned to the project based at least in part on the respective distances.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for searching and presenting undiscovered images. A system may receive a first user input specifying a search query for content from a client device. The system may initiate an image search in response to receiving the search query. The system may provide a first search result comprising a first list of images to the client device. The system may receive a second user input selecting an image from the first search result from the client device. The system may provide a second search result comprising a second list of images to the client device, based on the second user input, a similarity index, and a filtering criteria.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for relevance feedback with faceted search interface. A system provides a first search query to an image search engine for initiating an image search, where the first search query indicates a first search term. The system obtains image metadata from an image collection, and obtains a listing of query refinement terms associated with the first search query from the query refinement data structure. The system determines a listing of search results containing images with one or more facets associated with the listing of query refinement terms. The system then receives user input indicating selection of at least one of the one or more facets of an image in the listing of search results. The system provides a second search query using the first search term and a second search term indicating the selected one or more facets.

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for user drawing based image search. These aspects include an image retrieval system using a convolutional neural network trained to identify how users draw semantic concepts and using an image search engine to search against images having a similar concept. The aspects include mapping between concepts of the user drawing space and concepts of the image space such that images associated with the same concept are identified. For each input user drawing, the drawing is first processed through a concept classifier to identify a corresponding concept, and then through a feature extractor to form a corresponding feature vector. The results from the concept classifier and the feature extractor may be combined to search against a collection of images having a similar concept to determine a listing of images ranked by visual and semantic similarity to the input.