Speech model personalization via ambient context harvesting
AssigneeIntel Corporation
InventorsGabriel Amores, Guillermo Perez, Moshe Wasserblat, Michael Deisher, Loic Dufrensne de Virel
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Abstract
An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.
Claims20
An apparatus comprising:
- a microphone to capture audio;
- interface circuitry;
- machine readable instructions stored in a non-transitory memory;
- and
- programmable circuitry to at least one of execute or instantiate the machine readable instructions to:
- detect speech based on the audio collected by the microphone;
- identify situational data associated with the audio;
- determine a context associated with the audio based on the situational data;
- determine a confidence score indicative of a likelihood that the speech is associated with the context;
- recognize a dialog pattern based on the speech and the situational data, including comparing the speech to reference dialog data, wherein the dialog pattern includes a sequence of interactions in the reference dialog data;
- assign a similarity metric to the speech based on the comparison;
- classify the speech based on the dialog pattern and the similarity metric;
- and
- based on the confidence score satisfying a confidence threshold, add the speech and the similarity metric to a database.
At least one non-transitory memory comprising instructions to cause programmable circuitry to at least:
- detect speech from a user based on an audio collected by a microphone;
- identify a location associated with collection of the audio;
- determine a context associated with the audio based on the location;
- determine a confidence score indicative of a likelihood that the speech is associated with the context;
- recognize a structured interaction involving the user based on the speech and the location, including comparing the speech to reference dialog data, wherein the structured interaction includes a sequence of interactions in the reference dialog data;
- assign a similarity metric to the speech based on the comparison;
- classify the speech based on the structured interaction and the similarity metric;
- and
- add the speech and the similarity metric to a database, based on the confidence score satisfying a confidence threshold.
An apparatus comprising:
- a microphone to capture audio signals;
- interface circuitry;
- machine readable instructions stored in a non-transitory memory;
- and
- programmable circuitry to at least one of execute or instantiate the machine readable instructions to:
- identify a speaker associated with speech;
- identify situational data associated with the speech;
- determine a context associated with the audio based on the situational data;
- determine a confidence score indicative of a likelihood that the speech is associated with the context;
- recognize a dialog pattern based on the speech, the identity of the speaker, and the situational data, including comparing the speech to reference dialog data, wherein the dialog pattern includes a sequence of interactions in the reference dialog data;
- update training data based on the dialog pattern and the confidence score satisfying a confidence threshold, the training data to train a neural network model.
Dependencies are inferred from the claim text.