Snap Inc.

Ebay, Incorporated

Einav Itamar

Ido Guy

Arnon Dagan

Alan Bekker

Alexander Nus

Avinoam Omer

Raphael Bryl

Gadi Mikles

Noa Shimoni Barzilai

Itamar Schen

Yan Radovilsky

Jacob Assa

Jackie Assa

Nave Algarici

Systems and methods are provided for extracting entities from received speech. The systems and methods perform operations comprising receiving an audio file comprising speech input and processing, by a speech recognition engine, the audio file comprising the speech input to generate an initial character-based representation of the speech input. The operations further comprise processing, by an entity extractor, the initial character-based representation of the speech input to generate an estimated set of entities of the speech input. The operations further comprise generating, by the speech recognition engine, a textual representation of the speech input based on the estimated set of entities of the speech input.

Speech to entity

Systems and methods are provided for performing speech to intent classification. The systems and methods perform operations comprising: receiving an audio file comprising speech input; processing, by a speech recognition engine, the audio file comprising the speech input to generate an initial character-based representation of the speech input; processing, by an intent classifier, the initial character-based representation of the speech input to generate an estimated intent of the speech input; and generating, by the speech recognition engine, a textual representation of the speech input based on the estimated intent of the speech input.

Speech to intent

Disclosed are systems, methods, and non-transitory computer-readable media for automatic image selection for online product catalogs. An image selection system gathers feature data for images of an item included in listings posted to an online marketplace. The image selection system uses the feature data as input in a machine learning model to determine probability scores indicating an estimated probability that each image is suitable to represent the item. The machine learning model is trained based on a set of training images of the item that have been labeled to indicate whether they are suitable to represent the image. The image selection system compares the probability scores and selects an image to represent the item as a stock image based on the comparison.

Automatic image selection for online product catalogs

Growing community of inventors

Herzliya, Israel

Einav Itamar