METHOD AND APPARATUS FOR TRAINING LANGUAGE MODEL, AND METHOD AND APPARATUS FOR RECOGNIZING LANGUAGE
First Claim
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1. A method, comprising:
- generating a first training feature vector sequence and a second training feature vector sequence from training data;
performing forward estimation of a neural network based on the first training feature vector sequence, and performing backward estimation of the neural network based on the second training feature vector sequence; and
training a language model based on a result of the forward estimation and a result of the backward estimation.
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Abstract
A method and apparatus for training a language model, include generating a first training feature vector sequence and a second training feature vector sequence from training data. The method is configured to perform forward estimation of a neural network based on the first training feature vector sequence, and perform backward estimation of the neural network based on the second training feature vector sequence. The method is further configured to train a language model based on a result of the forward estimation and a result of the backward estimation.
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Citations
20 Claims
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1. A method, comprising:
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generating a first training feature vector sequence and a second training feature vector sequence from training data; performing forward estimation of a neural network based on the first training feature vector sequence, and performing backward estimation of the neural network based on the second training feature vector sequence; and training a language model based on a result of the forward estimation and a result of the backward estimation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 12)
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9. A method, comprising:
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generating a first input feature vector sequence and a second input feature vector sequence from input data; and performing forward estimation of a neural network based on the first input feature vector sequence and performing backward estimation of the neural network based on the second input feature vector sequence to estimate a result of recognizing the input data. - View Dependent Claims (10, 11, 20)
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13. An apparatus, comprising:
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a training data preprocessor configured to generate a first training feature vector sequence and a second training feature vector sequence from training data; and a language model trainer configured to train a neural network based language model based on the first training feature vector sequence and the second training feature vector sequence, perform forward estimation of the neural network with respect to the first training feature vector sequence, and perform backward estimation of the neural network with respect to the second training feature vector sequence. - View Dependent Claims (14, 15, 16, 17)
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18. An apparatus, comprising:
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an input data preprocessor configured to generate a first input feature vector sequence and a second input feature vector sequence from input data; and an input data recognizer configured to perform forward estimation of a neural network based on the first input feature vector sequence, and perform backward estimation of the neural network based on the second input feature vector sequence to estimate a result of recognizing the input data. - View Dependent Claims (19)
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Specification