Using Lattice-based Features for Out-of-Vocabulary Keywords Detection Task
Table 1: Comparison of two approaches for OOV KWS in terms of MTWV metric and speed for different AMs
['[BOLD] AM', '[BOLD] WER, [BOLD] %', '[BOLD] OOV decoder  [BOLD] MTWV', '[BOLD] OOV decoder  [BOLD] RTF', '[BOLD] Proxies  [BOLD] MTWV', '[BOLD] Proxies  [BOLD] RTF']
Experimental results show that the proposed OOV decoder significantly outperforms (in terms of MTWV metric and speed) The real time factor (RTF) was calculated per word. The comparison of the two OOV KWS approaches on the lattice-level fusion results of the nine different ASR systems fusion of the OOV decoder and the proxy-based search (in the point of low RTF) can provide a very fast search method that significantly outperforms the both approaches in MTWV.