Patent ID: 11922947
Assignee: SAS INSTITUTE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 28:
29. A computer-program product embodied in a non-transitory machine-readable storage medium storing computer instructions that, when executed by one or more processors, perform operations comprising:
constructing a transcript correction training data corpus comprising a plurality of labeled audio transcription training data samples, wherein each of the plurality of labeled audio transcription training data samples includes:
an incorrect audio transcription of a target piece of audio data, wherein the incorrect audio transcription is assigned an incorrect audio transcription label;
a correct audio transcription of the target piece of audio data, wherein the correct audio transcription is assigned a correct audio transcription label; and
a transcript correction identifier that, when applied to a model input comprising a likely incorrect audio transcript, defines a text-to-text transformation objective causing an audio transcript correction machine learning model to predict a corrected audio transcript based on the likely incorrect audio transcript;

configuring the audio transcript correction machine learning model based on a training of a machine learning text-to-text transformer model using the transcript correction training data corpus;
executing the audio transcript correction machine learning model within a speech-to-text post-processing sequence of a speech-to-text service based on the audio transcript correction machine learning model satisfying a minimum audio transcript correction efficacy value;
obtaining audio data comprising one or more utterances;
generating, via a speech-to-text machine learning model, a predicted audio transcript based on an input of the audio data;
generating, via the audio transcript correction machine learning model, an adjusted audio transcript of the predicted audio transcript based on an input of a task-specific instruction to the audio transcript correction machine learning model, wherein the audio transcript correction machine learning model identifies a task type of the instructional prefix component, wherein the task type of the instructional prefix component corresponds to the transcript correction identifier, and wherein the task-specific instruction includes:
an instructional prefix component comprising the transcript correction identifier; and
an input text string comprising the predicted audio transcript;

obtaining, from a memory, a set of weights and biases generated from the training of the machine learning text-to-text transformer model that corresponds to the transcript correction identifier, wherein the executing the audio transcript correction machine learning model includes using the set of weights and biases to generate the adjusted audio transcript.