Vail Systems, Inc.

Yu Zhou

Nikhita Sharma

Jordan Hosier

Neil Milstead

A system and method for identifying a speaker based on dual calculation of voiceprint match scores, using machine learned voiceprint sets and machine learned hashing models to reduce a voiceprint set, normalizing the joint scores, and performing user identification. The system and method include, among other things, a novel normalization technique designed for multitarget detection that considers scores between all enrolled negative list (NL) utterances and the normalization cohort as a single distribution. The system and method include machine learned hashing models to efficiently find a small subset of utterances from enrolled NL utterances and the normalization cohort that are most similar to the test utterance, so that the number of similarity score computations can be significantly reduced in identifying the speaker.

System and method using machine learned voiceprint sets for efficient determination of voice membership using enhanced score normalization and locality sensitive hashing

A system and method for detecting and resolving mis-transcriptions in a transcript generated by an automatic speech recognition system when transcribing spoken words. The system and method receive a machine language generated transcript of a speech signal by at least one of a first machine learning system and a second machine learning system, and analyze the machine language generated transcript to find a region of low confidence indicative of a mis-transcription and predict an improvement to the region of low confidence indicative of the mis-transcription. The system and method select a replacement word for the mis-transcription based on the predicted improvement to the region of low confidence and replace the mis-transcription by the replacement word to generate a corrected transcript.

Growing community of inventors

Naperville, IL, United States of America

Yu Zhou