Language model customization in speech recognition for speech analytics
First Claim
1. A method for performing voice analytics on interactions with an organization, comprising:
- training a customized language model for the organization by;
receiving, by a speech recognition engine, organization-specific training data and generic training data;
computing, by the speech recognition engine, a plurality of similarities between the generic training data and the organization-specific training data;
assigning, by the speech recognition engine, a plurality of weights to the generic training data through partitioning the generic training data into a plurality of partitions in accordance with the computed similarities wherein the computed similarities comprise a fixed set of one or more threshold similarities, associating a partition similarity with each of the partitions, the partition similarity corresponding to the average similarity of the data in the partition, and assigning a desired weight to each partition, the desired weight corresponding to the partition similarity of the partition;
combining, by the speech recognition engine, the generic training data with the organization-specific training data in accordance with the weights to generate customized training data;
training, by the speech recognition engine, the customized language model using the customized training data; and
outputting, by the speech recognition engine, the customized language model, the customized language model being configured to compute a likelihood of phrases in a medium;
receiving, by the speech recognition engine, an input speech from an interaction between a customer and an agent of the organization; and
performing voice analytics on the received input speech.
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Accused Products
Abstract
A method for generating a language model for an organization includes: receiving, by a processor, organization-specific training data; receiving, by the processor, generic training data; computing, by the processor, a plurality of similarities between the generic training data and the organization-specific training data; assigning, by the processor, a plurality of weights to the generic training data in accordance with the computed similarities; combining, by the processor, the generic training data with the organization-specific training data in accordance with the weights to generate customized training data; training, by the processor, a customized language model using the customized training data; and outputting, by the processor, the customized language model, the customized language model being configured to compute the likelihood of phrases in a medium.
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Citations
16 Claims
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1. A method for performing voice analytics on interactions with an organization, comprising:
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training a customized language model for the organization by; receiving, by a speech recognition engine, organization-specific training data and generic training data; computing, by the speech recognition engine, a plurality of similarities between the generic training data and the organization-specific training data; assigning, by the speech recognition engine, a plurality of weights to the generic training data through partitioning the generic training data into a plurality of partitions in accordance with the computed similarities wherein the computed similarities comprise a fixed set of one or more threshold similarities, associating a partition similarity with each of the partitions, the partition similarity corresponding to the average similarity of the data in the partition, and assigning a desired weight to each partition, the desired weight corresponding to the partition similarity of the partition; combining, by the speech recognition engine, the generic training data with the organization-specific training data in accordance with the weights to generate customized training data; training, by the speech recognition engine, the customized language model using the customized training data; and outputting, by the speech recognition engine, the customized language model, the customized language model being configured to compute a likelihood of phrases in a medium; receiving, by the speech recognition engine, an input speech from an interaction between a customer and an agent of the organization; and performing voice analytics on the received input speech. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A voice analytics system comprising:
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a speech model training system comprising; a processor; and memory coupled to the processor and storing instructions that, when executed by the processor, cause the processor to; receive organization-specific training data and generic training data; compute a plurality of similarities between the generic training data and the organization-specific training data; assign a plurality of weights to the generic training data through partitioning the generic training data into a plurality of partitions in accordance with the computed similarities wherein the computed similarities comprise a fixed set of one or more threshold similarities, associating a partition similarity with each of the partitions, the partition similarity corresponding to the average similarity of the data in the partition, and assigning a desired weight to each partition, the desired weight corresponding to the partition similarity of the partition; combine the generic training data with the organization-specific training data in accordance with the weights to generate customized training data; train a customized language model using the customized training data; and output the customized language model, the customized language model being configured to compute the likelihood of phrases in a medium; and a speech analytics system configured to; receive an input speech from an interaction between a customer and an agent of the organization; and perform voice analytics on the received input speech. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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Specification