“0920 - Lantian Li”版本间的差异
来自cslt Wiki
（以“Weekly Summary 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...”为内容创建页面） |
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| 第11行： | 第11行： | ||
3). Re-score for the four parts on the cohort set. | 3). Re-score for the four parts on the cohort set. | ||
| − | 4). Score ranking for each part and draw score-rank distrubution | + | 4). Score ranking for each part and draw score-rank distrubution diagrams. |
Next Week | Next Week | ||
| − | 1. Go on the task1 to explore the inherent law of re-scoring results and | + | 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". | reduce the error rate on the "Sensitive True Speaker"/"Sensitive Imp Speaker". | ||
2014年9月22日 (一) 10:22的最后版本
Weekly Summary
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 set in order for organizing the cohort set.
2). Make the verfication score results dividied into four parts. --"Real True Speaker"/"Sensitive True
Speaker"/"Sensitive Imp Speaker"/"Abosulte Imp Speaker".
3). Re-score for the four parts on the cohort set.
4). Score ranking for each part and draw score-rank distrubution diagrams.
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".
