End-to-end speech-to-dialog-act recognition
Table 2: DA classification error rates of baseline and unified model with given segmentation.
['Model', '1-best search WER', '1-best search LER ( [ITALIC] h=1)', '1-best search LER ( [ITALIC] h=5)', '[ITALIC] n-best beam search WER', '[ITALIC] n-best beam search LER ( [ITALIC] h=1)', '[ITALIC] n-best beam search LER ( [ITALIC] h=5)']
When trained with the ASR transcript, although the DA classifier is expected to adapt to the ASR output, it did not improve the accuracy in every case. A larger improvement is obtained by the proposed unified model using the ASR feature, which reduces the DA classification error rate. Note that the use of beam search and n-best hypotheses is more effective with the ASR feature. This is probably because the improved ASR performance with the beam search provides a better ASR feature representation. The improvement is statistically significant with h=5.