Microsoft Technology Licensing, LLC

William Isaac Hinthorn

Xuedong D Huang

Nanshan Zeng

Andreas Stolcke

Zhuo Chen

Takuya Yoshioka

Lijuan Qin

Dimitrios Basile Dimitriadis

Yu Shi

Chenguang Zhu

Liyang Lu

Ruochen Xu

A computer implemented method processes audio streams recorded during a meeting by a plurality of distributed devices. Operations include performing speech recognition on each audio stream by a corresponding speech recognition system to generate utterance-level posterior probabilities as hypotheses for each audio stream, aligning the hypotheses and formatting them as word confusion networks with associated word-level posteriors probabilities, performing speaker recognition on each audio stream by a speaker identification algorithm that generates a stream of speaker-attributed word hypotheses, formatting speaker hypotheses with associated speaker label posterior probabilities and speaker-attributed hypotheses for each audio stream as a speaker confusion network, aligning the word and speaker confusion networks from all audio streams to each other to merge the posterior probabilities and align word and speaker labels, and creating a best speaker-attributed word transcript by selecting the sequence of word and speaker labels with the highest posterior probabilities.

Speaker attributed transcript generation

A computer implemented method includes receiving audio signals representative of speech via multiple audio streams transmitted from corresponding multiple distributed devices, performing, via a neural network model, continuous speech separation for one or more of the received audio signals having overlapped speech, and providing the separated speech on a fixed number of separate output audio channels.

Processing overlapping speech from distributed devices

A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.

Automated meeting minutes generator

A computer implemented method includes receiving information streams on a meeting server from a set of multiple distributed devices included in a meeting, receiving audio signals representative of speech by at least two users in at least two of the information streams, receiving at least one video signal of at least one user in the information streams, associating a specific user with speech in the received audio signals as a function of the received audio and video signals, and generating a transcript of the meeting with an indication of the specific user associated with the speech.

Audio-visual diarization to identify meeting attendees

A computer implemented method includes receiving audio streams at a meeting server from two distributed devices that are streaming audio captured during an ad-hoc meeting between at least two users, comparing the received audio streams to determine that the received audio streams are representative of sound from the ad-hoc meeting, generating a meeting instance to process the audio streams in response to the comparing determining that the audio streams are representative of sound from the ad-hoc meeting, and processing the received audio streams to generate a transcript of the ad-hoc meeting.

Distributed device meeting initiation

Systems and methods for providing customized output based on a user preference in a distributed system are provided. In example embodiments, a meeting server or system receives audio streams from a plurality of distributed devices involved in an intelligent meeting. The meeting system identifies a user corresponding to a distributed device of the plurality of distributed devices and determines a preferred language of the user. A transcript from the received audio streams is generated. The meeting system translates the transcript into the preferred language of the user to form a translated transcript. The translated transcript is provided to the distributed device of the user.

Customized output to optimize for user preference in a distributed system

A computer implemented method includes receiving multiple channels of audio from three or more microphones detecting speech from a meeting of multiple users, localizing speech sources to determine an approximate direction of arrival of speech from a user, using a speech unmixing model to select two channels corresponding to a primary and a secondary microphone, and sending the two selected channels to a meeting server for generation of a speaker attributed meeting transcript.

Audio stream processing for distributed device meeting

A computer implemented method includes receiving audio signals representative of speech via multiple audio channels transmitted from corresponding multiple distributed devices, designating one of the audio channels as a reference channel, and for each of the remaining audio channels, determine a difference in time from the reference channel, and correcting each remaining audio channel by compensating for the corresponding difference in time from the reference channel.

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William Isaac Hinthorn