A Unified Linear-Time Framework for Sentence-Level Discourse Parsing
Table 4: Speed comparison of our systems with other open-sourced systems.
['[BOLD] System', '[BOLD] Speed (Sents/s)', '[BOLD] Speedup']
As noted earlier, both our segmenter and parser operate in linear time with respect to the number of input units. We test all the systems with the same 100 sentences randomly selected from our test set on our machine (CPU: Intel Xeon W-2133, GPU: NVIDIA GTX 1080Ti). We include the model loading time for all the systems. In addition, CODRA’s DCRF parser has a O(n3) inference time. Our segmenter is 6.8x faster than SPADE. Compared to CODRA (the fastest parser as of yet), our parser is 3.9x faster. Finally, our end-to-end system is 5.9x faster than the fastest system out there (SPADE), making our system not only effective but also highly efficient. Even when tested only on CPU, our model is faster than all the other models.