Gm Global Technolgoy Operations, Inc.

Shazam Entertainment Limited

Ognjen Todic

Jane MacFarlane

Stephen C Habermas

Kai-Ten Feng

Methods and systems for performing audio synchronization with corresponding textual transcription and determining confidence values of the timing-synchronization are provided. Audio and a corresponding text (e.g., transcript) may be synchronized in a forward and reverse direction using speech recognition to output a time-annotated audio-lyrics synchronized data. Metrics can be computed to quantify and/or qualify a confidence of the synchronization. Based on the metrics, example embodiments describe methods for enhancing an automated synchronization process to possibly adapted Hidden Markov Models (HMMs) to the synchronized audio for use during the speech recognition. Other examples describe methods for selecting an appropriate HMM for use.

Methods and systems for performing synchronization of audio with corresponding textual transcriptions and determining confidence values of the synchronization

An automated speech recognition filter is disclosed. The automated speech recognition filter device provides a speech signal to an automated speech platform that approximates an original speech signal as spoken into a transceiver by a user. In providing the speech signal, the automated speech recognition filter determines various models representative of a cumulative signal degradation of the original speech signal from various devices along a transmission signal path and a reception signal path between the transceiver and a device housing the filter. The automated speech platform can thereby provide an audio signal corresponding to a context of the original speech signal.

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San Francisco, CA, United States of America

Ognjen Todic