Systems and methods for separating and identifying audio in an audio file using machine learning
AssigneeThe MITRE Corporation
InventorYuan-Jun WEI
Life of this patent
Estimating the term…
Loading patent…
AssigneeThe MITRE Corporation
InventorYuan-Jun WEI
Estimating the term…
Disclosed herein are systems and methods for processing an audio file to perform audio Segmentation and Speaker Role Identification (SRID) by training low level classifier and high level clustering components to separate and identify audio from different sources in an audio file by unifying audio separation and automatic speech recognition (ASR) techniques in a single system. Segmentation and SRID can include separating audio in an audio file into one or more segments, based on a determination of the identity of the speaker, category of the speaker, or source of audio in the segment. In one or more examples, the disclosed systems and methods use machine learning and artificial intelligence technology to determine the source of segments of audio using a combination of acoustic and language information. In some examples, the acoustic and language information is used to classify audio in each frame and cluster the audio into segments.
A method for predicting a speaker role of a source of audio, the method comprising:
A system for predicting a speaker role of a source of audio, the system comprising one or more processors and a memory storing one or more computer programs, the one or more computer programs including instructions that when executed by the one or more processors cause the system to:
A non-transitory computer readable storage medium storing one or more programs for processing an audio file, the one or more programs configured to be executed by one or more processors and including instructions for:
Dependencies are inferred from the claim text.