Generating Sequences WithRecurrent Neural Networks
Table 4: Handwriting Synthesis Results. All results recorded on the validation set. ‘Log-Loss’ is the mean value of L(x) in nats. ‘SSE’ is the mean sum-squared-error per data point.
['Regularisation', 'Log-Loss', 'SSE']
The regularised network appears to generate slightly more realistic sequences, although the difference is hard to discern by eye. Both networks performed considerably better than the best prediction network. In particular the sum-squared-error was reduced by 44%. This is likely due in large part to the improved predictions at the ends of strokes, where the error is largest.