Abstract: Systems and methods are provided for acquiring training data and building an organizational-based language model based on the training data. In organizational data is generated via one or more applications associated with an organization, the collected organizational data is aggregated and filtered into training data that is used for training an organizational-based language model for speech processing based on the training data.

Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.

Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.

Abstract: A context-aware transcription system includes a language model preparation service that retrieves meeting-specific data prior to or during a meeting. The language model preparation service utilizes the meeting-specific data to generate a meeting-specific statistical language model. A speech transcription service can utilize the meeting-specific statistical language model to generate a transcription of audio generated by attendees of a meeting. The system can transmit the transcription to computing devices associated with meeting attendees during the meeting for presentation in a user interface in real time. The language model preparation service can generate the meeting-specific statistical language model in response to receiving a pre-meeting signal. The pre-meeting signal can be generated a predetermined time prior to meetings according to a schedule.

Abstract: Provided is a system and method for acquiring training data and building an organizational-based language model based on the training data. In one example, the method may include collecting organizational data that is generated via one or more applications associated with an organization, aggregating the collected organizational data with previously collected organizational data to generate aggregated organizational training data, training an organizational-based language model for speech processing based on the aggregated organizational training data, and storing the trained organizational-based language model.

Abstract: A context-aware transcription system includes a language model preparation service that retrieves meeting-specific data prior to or during a meeting. The language model preparation service utilizes the meeting-specific data to generate a meeting-specific statistical language model. A speech transcription service can utilize the meeting-specific statistical language model to generate a transcription of audio generated by attendees of a meeting. The system can transmit the transcription to computing devices associated with meeting attendees during the meeting for presentation in a user interface in real time. The language model preparation service can generate the meeting-specific statistical language model in response to receiving a pre-meeting signal. The pre-meeting signal can be generated a predetermined time prior to meetings according to a schedule.