Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition
Table 3: Ranked percentiles of improvement in intent recognition. The improvement is determined for each intent class individually. Intent classes are sorted and binned into percentiles, for each bin we report the minimum improvement for intents in the bin.
['[BOLD] Intent classes [%]', '[BOLD] Min. improvement [%]']
The proposed algorithm finds 658 549 intents in all conversations, covering 4.1% of all (62 450 768) words, whereas the baseline algorithm finds 526 356 intents, covering 3.3% of all words. Therefore, the increase in intent recognition of the method is 25.1% by rescoring 8.3% of all annotated words (0.34% of all words). We see that half of intents gain at least 35.7% of improvement, while 20% of all intents gain at least 83.5%.