Microsoft Technology Licensing, LLC

Zoltan Romocsa

Amit Kumar Agarwal

Christopher Hakan Basoglu

Shuangyu Chang

Ziad Al Bawab

Anand U Desai

Nathan E Wohlgemuth

Hosam Adel Khalil

Shalendra Chhabra

Sayan Dev Pathak

Piyush Behre

Veljko Miljanic

Rishi Girish

Sharman W Tan

Amy Parag Shah

Michael J Shelton

Aadyot Bhatnagar

Halley Weitzman

Mikhail Raer

Skyler Michael Anderson

Ayush Vikram

Tomas Bergl

Mykola Denysiuk

Andrii Matukhno

Some disclosed embodiments are directed to obtaining a decoded audio data including a spoken language utterance recognized in audio data and identifying a disfluency in the decoded audio data. Upon determining that correcting the disfluency would improve a readability score of the decoded audio data, the system generates a particular correction to correct the disfluency and applies the particular correction to the decoded audio data. Then, an updated decoded audio data is generated which reflects the particular correction. The updated decoded audio data has improved readability over the decoded audio data.

Systems and methods for GPT guided neural punctuation for conversational speech

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

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. The pre-meeting signal might also, or alternately, be generated in response to the receipt of meeting change event notifications before or during meetings that describe changes to the meetings.

Context-aware real-time meeting audio transcription

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Kenmore, WA, United States of America

Zoltan Romocsa