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{Lukáš Burget Miroslav Skácel Igor Szöke}

Abstract
The primary system we submitted was composed of 11 subsystems as the required run. 3 subsystems are based on Acoustic Keyword Spotting (AKWS) and 8 on Dynamic Time Warping (DTW). The AKWS systems were based only on phoneme posteriors while the DTW subsystems were based on both phoneme posteriors and Bottle-Neck features (BN) as input. The underlying phoneme posterior estimators / bottle-neck feature extractors were both in-language (Czech) and out-of-language (other 4 languages). We also performed experiments on T1/T2/T3 types of query, system calibration and fusion based on binary logistic regression
Benchmarks
| Benchmark | Methodology | Metrics |
|---|---|---|
| keyword-spotting-on-quesst | BUT (g-LID) | MinCnxe: 0.929 |
| keyword-spotting-on-quesst | BUT (AKWS-T3-cz) | MinCnxe: 0.673 |
| keyword-spotting-on-quesst | BUT (g-best_single) | MinCnxe: 0.533 |
| keyword-spotting-on-quesst | BUT (g-bigfusionnoside ) | MinCnxe: 0.486 |
| keyword-spotting-on-quesst | BUT (AKWS-cz) | MinCnxe: 0.641 |
| keyword-spotting-on-quesst | BUT (p-bigfusion) | MinCnxe: 0.461 |
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