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Evaluation and Optimization of Computational Costs in Speaker Recognition Systems
 Gregušová, Sabína ; Silnova, Anna (oponent) ; Rohdin, Johan Andréas (vedoucí práce)
The goal of this thesis is to propose an evaluation metric that includes computational costs. Computational costs generally do not pose a problem in research, but it can become problematic in a commercial production system, where speed is essential. The proposed metric extends existing evaluation framework from NIST and adds parameter for time unit and time unit cost. These metrics are applied on real ASV and experiments show the potential for further research and possible use. The experiments focus on reducing the computational cost by posing a limit on maximum length of the utterance, but also limiting number of frames for x-vector extraction. Both optimizations reduced the computational costs and reached favorable results for the new metrics. Finally, experiments' results are compared and each system modification is ranked according to the new metrics.
Úplný záznam
Evaluation and Optimization of Computational Costs in Speaker Recognition Systems
 Gregušová, Sabína ; Silnova, Anna (oponent) ; Rohdin, Johan Andréas (vedoucí práce)
The goal of this thesis is to propose an evaluation metric that includes computational costs. Computational costs generally do not pose a problem in research, but it can become problematic in a commercial production system, where speed is essential. The proposed metric extends existing evaluation framework from NIST and adds parameter for time unit and time unit cost. These metrics are applied on real ASV and experiments show the potential for further research and possible use. The experiments focus on reducing the computational cost by posing a limit on maximum length of the utterance, but also limiting number of frames for x-vector extraction. Both optimizations reduced the computational costs and reached favorable results for the new metrics. Finally, experiments' results are compared and each system modification is ranked according to the new metrics.
Úplný záznam

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