Performance evaluation in open-set speaker identification

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Abstract

The concern in this study is the approach to evaluating the performance of the open-set speaker identification process. In essence, such a process involves first identifying the speaker model in the database that best matches the given test utterance, and then determining if the test utterance has actually been produced by the speaker associated with the best-matched model. Whilst, conventionally, the performance of each of these two sub-processes is evaluated independently, it is argued that the use of a measure of performance for the complete process can provide a more useful basis for comparing the effectiveness of different systems. Based on this argument, an approach to assessing the performance of open-set speaker identification is considered in this paper, which is in principle similar to the method used for computing the diarisation error rate. The paper details the above approach for assessing the performance of open-set speaker identification and presents an analysis of its characteristics. © 2011 Springer-Verlag.

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APA

Malegaonkar, A., & Ariyaeeinia, A. (2011). Performance evaluation in open-set speaker identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6583 LNCS, pp. 106–112). https://doi.org/10.1007/978-3-642-19530-3_10

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