Closed Sathiyakugan closed 5 years ago
The Sentence Error Rate (SER%) is the classification error rate computed at sentence level. In practice, we take a decision based on windows of 200 ms shifted by 10 ms and we average the posterior probabilities over all these frames composing the sentence. The class with the highest average probability is the winner and it is compared with the reference ground truth. This procedure is repeated for all the sentences of the test set.
Best,
Mirco
On Tue, 6 Aug 2019 at 09:18, Sathiyakugan notifications@github.com wrote:
Since the paper indicates that Sentence error rate could you please explain about the Sentence error rate on Speaker Identification ?
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Since the paper indicates that Sentence error rate, could you please explain about the Sentence error rate on Speaker Identification?