Bubble splitting for compact acoustic modeling
First Claim
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1. A method for constructing acoustic models for use in a speech recognizer, comprising:
- partitioning speech data from a plurality of training speakers according to at least one speech related criteria, wherein the step of partitioning speech data further comprises partitioning the speech data into male group data and female group data by labeling the speech data according to gender of the training speakers during training, and further partitioning the male group data by vocal tract length normalization factor for only the male group, and partitioning the female group data by vocal tract length normalization factor for only the female group;
grouping together the partitioned speech data from training speakers having similar speech characteristics, including gender and gender-specific vocal tract length normalization factor; and
training an acoustic bubble model for each group using the speech data within the group.
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Abstract
An improved method is provided for constructing compact acoustic models for use in a speech recognizer. The method includes: partitioning speech data from a plurality of training speakers according to at least one speech related criteria (i.e., vocal tract length); grouping together the partitioned speech data from training speakers having a similar speech characteristic; and training an acoustic bubble model for each group using the speech data within the group.
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Citations
13 Claims
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1. A method for constructing acoustic models for use in a speech recognizer, comprising:
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partitioning speech data from a plurality of training speakers according to at least one speech related criteria, wherein the step of partitioning speech data further comprises partitioning the speech data into male group data and female group data by labeling the speech data according to gender of the training speakers during training, and further partitioning the male group data by vocal tract length normalization factor for only the male group, and partitioning the female group data by vocal tract length normalization factor for only the female group; grouping together the partitioned speech data from training speakers having similar speech characteristics, including gender and gender-specific vocal tract length normalization factor; and training an acoustic bubble model for each group using the speech data within the group. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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Specification