“09-30 Lantian Li”版本间的差异
(以“1. To go on studying a scoring method on GMM-UBM aiming to design a cohort reference speaker models. 1). Implement the K-means algorithem to cluster the training se...”为内容创建页面) |
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1. To go on studying a scoring method on GMM-UBM aiming to design a cohort reference speaker models. | 1. To go on studying a scoring method on GMM-UBM aiming to design a cohort reference speaker models. | ||
− | 1). | + | 1). On the basis of testing on a small scale, a total-batch experiment was made. |
− | + | The result for "true speaker" shows that there exists a score gap between the real-speaker and cohort | |
− | + | speaker. Besides, the variance from the real-true-speaker is larger than the sen-true-speaker based on the | |
− | + | cohort set. For imposter-speaker having the similar result, However, it does not meet the original hypothesis | |
− | + | that if the speaker is not the true speaker, it may have the similar scoring between this hypothesis | |
+ | |||
+ | speaker model and corhort models. But experimental result shows that there still has a gap. | ||
Next Week | Next Week |
2014年9月29日 (一) 02:32的版本
1. To go on studying a scoring method on GMM-UBM aiming to design a cohort reference speaker models.
1). On the basis of testing on a small scale, a total-batch experiment was made.
The result for "true speaker" shows that there exists a score gap between the real-speaker and cohort
speaker. Besides, the variance from the real-true-speaker is larger than the sen-true-speaker based on the
cohort set. For imposter-speaker having the similar result, However, it does not meet the original hypothesis
that if the speaker is not the true speaker, it may have the similar scoring between this hypothesis
speaker model and corhort models. But experimental result shows that there still has a gap.
Next Week
1. Go on the task1 to explore the inherent law of re-scoring results and use the cohort set to
reduce the error rate on the "Sensitive True Speaker"/"Sensitive Imp Speaker".