Sequence Discriminative Training for Deep Learning based Acoustic Keyword Spotting
TABLE IV: Post Processing of Sequence Discriminative Training Systems
['Model (Crit.)', 'Post', 'EER', 'RTF']
However, because its speed is much faster, the posterior smoothing method can be implemented as a pre-selection procedure of the speech corpus, and the kw-filler can be applied as a verification procedure. Such strategies improve the efficiency of spoken document retrieval systems, especially large amounts of data should always be waded through by these systems. In CTC, the proposed MED method is also tested. It shows perceptibly worse performance than kw-filler, but better efficiency. The slower speed of the CTC system versus the LF-bMMI system stems from the model inference of LSTM for CTC is slower than that of TDNN for LF-bMMI.