Microsoft Technology Licensing, LLC

Anand U Desai

Shuangyu Chang

Ziad Al Bawab

Amit Kumar Agarwal

Christopher Hakan Basoglu

Zoltan Romocsa

Michael Levit

Marcus Jon Jager

Rishi Girish

Xin Meng

Suyash Choudhury

Dhiresh Rawal

Tao Li

Cem Aksoylar

Ananth Rampura Sheshagiri Rao

Nathan E Wohlgemuth

Hosam Adel Khalil

Veljko Miljanic

Aadyot Bhatnagar

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.

Organizational-based language model generation

A system includes acquisition of meeting data associated with a meeting, determination of a plurality of meeting participants based on the acquired meeting data, acquisition of e-mail data associated with each of the plurality of meeting participants, generation of a meeting language model based on the acquired e-mail data and the meeting data, and transcription of audio associated with the meeting based on the meeting language model.

Meeting-adapted language model for speech recognition

A system includes acquisition of a domain grammar, determination of an interpolated grammar based on the domain grammar and a base grammar, determination of a delta domain grammar based on an augmented first grammar and the interpolated grammar, determination of an out-of-vocabulary class based on the domain grammar and the base grammar, insertion of the out-of-vocabulary class into a composed transducer composed of the augmented first grammar and one or more other transducers to generate an updated composed transducer, composition of the delta domain grammar and the updated composed transducer, and application of the composition of the delta domain grammar and the updated composed transducer to an output of an acoustic model.

Online language model interpolation for automatic speech recognition

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.

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Anand U Desai