CUHK System for QUESST Task of MediaEval 2014
This paper describes a spoken keyword search system developed at the Chinese University of Hong Kong (CUHK) for the query by example search on speech (QUESST) task of MediaEval 2014. This system utilizes posterior features and dynamic time warping (DTW) for keyword matching. Multiple types of posterior features are generated with different tokenizers, and then fused by a linear combination on the DTW distance matrices. The main contribution of this year’s system is a multiview segment clustering (MSC) approach for unsupervised ASM tokenizer construction. The Cnxe and ATWV of our submitted results on the Evaluation set are 0.682 and 0.412, respectively.
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| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Keyword Spotting | QUESST | CUHK(all the queries) System №2 | Cnxe | 0.638 | # 3 | |
| MinCnxe | 0.585 | # 4 | ||||
| ATWV | 0.412 | # 1 | ||||
| MTWV | 0.413 | # 2 | ||||
| Keyword Spotting | QUESST | CUHK(all the queries) System №1 | Cnxe | 0.682 | # 5 | |
| MinCnxe | 0.659 | # 10 | ||||
| ATWV | 0.412 | # 1 | ||||
| MTWV | 0.413 | # 2 |
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