The role of context in neural pitch accent detection in English
Table 1: Development set accuracy of speech-only model variants using different input contexts and architectures. Greater input context helps, and including LSTM layers works better than just CNN layers.
['[BOLD] Context', '[BOLD] Architecture', '[BOLD] Acc (%)']
The results confirm our hypotheses that it should help to include more input context (full utterances rather than only three tokens as in SVS18) and to use an LSTM to permit better use of that context. Note that our full utterance CNN-only model actually has more parameters than the CNN+LSTM model (∼14m, vs. ∼12m), so the improvements of the latter are not just due to model size.