Neural network training apparatus and method, and speech recognition apparatus and method
First Claim
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1. A neural network training apparatus comprising:
- a processor comprisinga primary trainer configured toperform a primary training of a neural network model using clean training data and target data corresponding to the clean training data, andgenerate, as an output of the primary training, a probability distribution of an output class for the clean training data;
a mixer configured to create noisy training data by mixing the clean training data and training noise data or adding distorted data to the clean training data; and
a secondary trainer configured to perform a secondary training of the neural network model on which the primary training has been performed using the noisy training data and the probability distribution of the output class for the clean training data that is generated during the primary training of the neural network model.
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Abstract
A neural network training apparatus includes a primary trainer configured to perform a primary training of a neural network model based on clean training data and target data corresponding to the clean training data; and a secondary trainer configured to perform a secondary training of the neural network model on which the primary training has been performed based on noisy training data and an output probability distribution of an output class for the clean training data calculated during the primary training of the neural network model.
32 Citations
20 Claims
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1. A neural network training apparatus comprising:
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a processor comprising a primary trainer configured to perform a primary training of a neural network model using clean training data and target data corresponding to the clean training data, and generate, as an output of the primary training, a probability distribution of an output class for the clean training data; a mixer configured to create noisy training data by mixing the clean training data and training noise data or adding distorted data to the clean training data; and a secondary trainer configured to perform a secondary training of the neural network model on which the primary training has been performed using the noisy training data and the probability distribution of the output class for the clean training data that is generated during the primary training of the neural network model. - View Dependent Claims (2, 3, 4, 5)
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6. A neural network training method comprising:
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performing, by a processor, a primary training of a neural network model using clean training data and target data corresponding to the clean training data; generating, by the processor and as an output of the primary training, a probability distribution of an output class for the clean training data; creating, by the processor, noisy training data by mixing the clean training data and training noise data or adding distorted data to the clean training data; and performing, by the processor, a secondary training of the neural network model on which the primary training has been performed using the noisy training data and the probability distribution of the output class for the clean training data that is generated during the primary training of the neural network model. - View Dependent Claims (7, 8, 9, 10, 11)
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12. A speech recognition apparatus comprising:
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a processor comprising a feature extractor configured to extract a feature of noisy speech data; and a phoneme probability calculator configured to calculate a probability of a phoneme corresponding to the extracted feature using an acoustic model; wherein the processor is further configured to generate the acoustic model by performing a primary training based on speech training data and a phoneme sequence corresponding to the speech training data using a first objective function that obtains the phoneme sequence from the speech training data, generating noisy speech training data by mixing the speech training data and training noise data or adding distorted data to the speech training data, performing a secondary training based on the noisy speech training data and a probability distribution of an output class for the speech training data calculated during the primary training of the acoustic model using a second objective function that obtains the probability distribution of the output class for the speech training data from the noisy speech training data. - View Dependent Claims (13, 14, 15, 16)
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17. A neural network training apparatus comprising:
a processor comprising a primary trainer configured to perform a primary training of a neural network model using clean training data and hard target data; a mixer configured to generate noisy training data from the clean training data; and a secondary trainer configured to perform a secondary training of the neural network model on which the primary training has been performed using the noisy training data and soft target data obtained as an output of the primary training of the neural network model. - View Dependent Claims (18, 19, 20)
Specification