Soundhound, Inc.

Joel Gedalius

Bernard Mont-Reynaud

Jun Huang

Kiran Garaga Lokeswarappa

Aaron Master

A computer-implemented method is provided. The method including receiving speech audio of dictation associated with a user ID, deriving acoustic features from the speech audio, storing the derived acoustic features in a user profile associated with the user ID, receiving a request for acoustic features through an application programming interface (API), the request including the user ID, and sending the derived acoustic features through the API.

Deriving acoustic features and linguistic features from received speech audio

A method is provided for advertisement selection. The method includes recognizing words from user speech over a large number of interactions, computing a number of unique words uttered during the interactions, classifying the user by the number of unique words uttered during the interactions, and selecting an advertisement targeted to the classified users.

Advertisement selection by linguistic classification

A system and method are provided for adding user characterization information to a user profile by analyzing user's speech. User properties such as age, gender, accent, and English proficiency may be inferred by extracting and deriving features from user speech, without the user having to configure such information manually. A feature extraction module that receives audio signals as input extracts acoustic, phonetic, textual, linguistic, and semantic features. The module may be a system component independent of any particular vertical application or may be embedded in an application that accepts voice input and performs natural language understanding. A profile generation module receives the features extracted by the feature extraction module and uses classifiers to determine user property values based on the extracted and derived features and store these values in a user profile. The resulting profile variables may be globally available to other applications.

Method and system for building an integrated user profile

Systems and methods for determining underplayed or overplayed items are provided herein. Instructions stored in memory are executed by a processor to: calculate short term scores for radio data and music identification service data of the items, determine linear distance and logarithmic distance between radio virtual radio plays per days on one million stations (VRPDOMS) and identification VRPDOMS of the items, identify and eliminate items lacking minimum requisite number of radio VRPDOMS or identification VRPDOMS, and sort the items by largest linear distance or largest logarithmic distance first. The sorted items are then transmitted to the computing device.

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Baltimore, MD, United States of America

Joel Gedalius