ISCA Archive Interspeech 2014
ISCA Archive Interspeech 2014

Graph-based re-ranking using acoustic feature similarity between search results for spoken term detection on low-resource languages

Hung-yi Lee, Yu Zhang, Ekapol Chuangsuwanich, James R. Glass

Acoustic feature similarity between search results has been shown to be very helpful for the task of spoken term detection (STD). A graph-based re-ranking approach for STD has been proposed based on the concept that search results, which are acoustically similar to other results with higher confidence scores, should have higher scores themselves. In this approach, the similarity between all search results of a given term are considered as a graph, and the confidence scores of the search results propagate through this graph. Since this approach can improve STD results without any additional labelled data, it is especially suitable for STD on languages with limited amounts of annotated data. However, its performance has not been widely studied on benchmark corpora. In this paper, we investigate the effectiveness of the graph-based re-ranking approach on limited language data from the IARPA Babel program. Experiments on the low-resource languages, Assamese, Bengali and Lao, show that graph-based re-ranking improves STD systems using fuzzy matching, and lattices based on different kinds of units including words, subwords, and hybrids.


doi: 10.21437/Interspeech.2014-526

Cite as: Lee, H.-y., Zhang, Y., Chuangsuwanich, E., Glass, J.R. (2014) Graph-based re-ranking using acoustic feature similarity between search results for spoken term detection on low-resource languages. Proc. Interspeech 2014, 2479-2483, doi: 10.21437/Interspeech.2014-526

@inproceedings{lee14c_interspeech,
  author={Hung-yi Lee and Yu Zhang and Ekapol Chuangsuwanich and James R. Glass},
  title={{Graph-based re-ranking using acoustic feature similarity between search results for spoken term detection on low-resource languages}},
  year=2014,
  booktitle={Proc. Interspeech 2014},
  pages={2479--2483},
  doi={10.21437/Interspeech.2014-526},
  issn={2308-457X}
}