Abstract: A method for speech recognition biasing includes receiving, from an application executing on a user device, at a speech service interface, a speech recognition request requesting a transcription of an utterance. The speech recognition request includes audio data encoding the utterance and configuration parameters for biasing a speech recognition model based on context data. The method includes processing, using the speech recognition model, the audio data to generate speech recognition scores for speech elements and determining context scores for the speech elements based on the configuration parameters and the context data. The method includes biasing the speech recognition scores using the context scores. The method also includes determining the transcription for the utterance based on the biased speech recognition scores.

Abstract: The present disclosure includes systems and methods for classifying user content (e.g., spam) within an online community by determining user specific signals and content specific signals, the systems and methods comprising: a user interface module configured to receive user content from the online community, a social signal processing module configured to determine signals from the user content, a user and content classifying module configured to classify user content and configured to compute a decision on the user content, a user content labeling module configured to label the user content, and an execution module configured to execute the decision.