Obfuscating training data
AssigneeLongsand Limited
InventorsAbigail Betley, David Pye, Milky Tefera Asefa
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Abstract
Examples disclosed herein involve obfuscating training data. An example method includes computing a sequence of acoustic features from audio data of training data, the training data comprising the audio data and a corresponding text transcript; mapping the acoustic features to acoustic model states to generate annotated feature vectors, the annotated feature vectors comprising the acoustic features and corresponding context from the text transcript; and providing a randomized sequence of the annotated feature vectors as obfuscated training data to an audio analysis system.
Claims15
A method to obfuscate training data, the method comprising:
- computing a sequence of acoustic features from audio data of the training data, the training data comprising the audio data and a corresponding text transcript;
- mapping the acoustic features to acoustic model states to generate annotated feature vectors, the annotated feature vectors comprising the acoustic features and corresponding states, the states corresponding to context from the text transcript;
- and
- providing a randomized sequence of the annotated feature vectors as obfuscated training data to an audio analysis system.
An apparatus comprising:
- an acoustic feature generator to compute acoustic features from an audio file of training data;
- a state identifier to:
- identify states of the acoustic features, the states being associated with an acoustic model of an audio analysis system and determined from context of a text transcript of the training data corresponding to the audio file, and
- generate annotated feature vectors including the acoustic features and the states of the acoustic features;
- and
- a randomizer to randomize the annotated feature vectors such that subject matter of the training data is obfuscated.
A non-transitory computer readable storage medium comprising instructions that, when executed, cause a machine to at least:
- analyze audio data to determine acoustic features from the audio data;
- map the acoustic features to states of an acoustic model of an audio analysis system and generate annotated feature vectors comprising the states and corresponding context from text transcripts of the audio data;
- and
- provide randomized annotated feature vectors to the audio analysis system to obfuscate confidential information in the audio data and the text transcript, the randomized annotated feature vectors from the set of generated annotated feature vectors.
Dependencies are inferred from the claim text.