ELiRF at MediaEval 2014: Query by Example Search on Speech Task (QUESST)
In this paper, we present the systems that the Natural Language Engineering and Pattern Recognition group (ELiRF) has submitted to the MediaEval 2014 Query by Example Search on Speech task. All of them are based on a Subsequence Dynamic Time Warping algorithm and do not use any other information from outside the task (zero-resources systems).
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| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Keyword Spotting | QUESST | ELiRF Fusion+Length(All Queries) | Cnxe | 0.6023 | # 1 | |
| MinCnxe | 0.5977 | # 6 | ||||
| ATWV | 0.3792 | # 5 | ||||
| MTWV | 0.3801 | # 6 | ||||
| Keyword Spotting | QUESST | ELiRF Fusion(All Queries) | Cnxe | 0.6125 | # 2 | |
| MinCnxe | 0.6062 | # 7 | ||||
| ATWV | 0.3896 | # 4 | ||||
| MTWV | 0.3952 | # 5 |
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