Abstract: A virtual assistant processes natural language expressions according to grammar rules created by domain providers. The virtual assistant uniquely identifies each of a multiplicity of users and stores values of grammar slots filled by natural language expressions from each user. The virtual assistant stores histories of slot values and computes statistics from the history. The virtual assistant provider, or a classification client, provides values of attributes of users as labels for a machine learning classification algorithm. The algorithm processes the grammar slot values and labels to compute probability distributions for unknown attribute values of users. A network effect of users and domain grammars make the virtual assistant useful and provides increasing amounts of data that improve classification accuracy and usefulness.

Abstract: A virtual assistant processes natural language expressions according to grammar rules created by domain providers. The virtual assistant uniquely identifies each of a multiplicity of users and stores values of grammar slots filled by natural language expressions from each user. The virtual assistant stores histories of slot values and computes statistics from the history. The virtual assistant provider, or a classification client, provides values of attributes of users as labels for a machine learning classification algorithm. The algorithm processes the grammar slot values and labels to compute probability distributions for unknown attribute values of users. A network effect of users and domain grammars make the virtual assistant useful and provides increasing amounts of data that improve classification accuracy and usefulness.

Abstract: A method for identifying with a broadcast stream. That method includes receiving one or more broadcast streams, from which it generates and stores an audio fingerprint of a selected portion of each received broadcast stream. A query is received, and the method generates an audio fingerprint of the query. From that point, the method continues by identifying audio content from the query, using the query audio fingerprint and a database of indexed audio content. The method concludes by identifying the source of the query using the query audio fingerprint and the stored audio fingerprints. Embodiments of the method further include predictively caching audio fingerprint sequences and corresponding audio item identifiers from a server after storing audio fingerprints extracted from the broadcast stream; and using the predictively cached audio fingerprint sequences to identify an audio item within the audio signal based on at least some additional audio fingerprints of the audio signal.

Abstract: A method for identifying with a broadcast stream. That method includes receiving one or more broadcast streams, from which it generates and stores an audio fingerprint of a selected portion of each received broadcast stream. A query is received, and the method generates an audio fingerprint of the query. From that point, the method continues by identifying audio content from the query, using the query audio fingerprint and a database of indexed audio content. The method concludes by identifying the source of the query using the query audio fingerprint and the stored audio fingerprints.