In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

The ratio of correct `translations' (matches) was used as an evaluation measure. 
 Question: What evaluation metric do they use?
Accuracy

A “coding scheme” is defined, which is a set of labels, annotations, or codes that items in the corpus may have. Schemes include formal definitions or procedures, and often include examples, particularly for borderline cases. Next, coders are trained with the coding scheme, which typically involves interactive feedback. Training sometimes results in changes to the coding scheme, in which the first round becomes a pilot test. Then, annotators independently review at least a portion of the same items throughout the entire process, with a calculation of “inter-annotator agreement” or “inter-rater reliability.” Finally, there is a process of “reconciliation” for disagreements, which is sometimes by majority vote without discussion and other times discussion-based. 
 Question: What are the core best practices of structured content analysis?
“coding scheme” is defined coders are trained with the coding scheme Training sometimes results in changes to the coding scheme calculation of “inter-annotator agreement” or “inter-rater reliability.” there is a process of “reconciliation” for disagreements

Traditional text-to-speech (TTS) systems are composed of complex pipelines BIBREF0 , these often include accoustic frontends, duration model, acoustic prediction model and vocoder models. Neural text-to-speech systems have garnered large research interest in the past 2 years. The first to fully explore this avenue of research was Google's tacotron BIBREF1 system. The architecture of our model utilizes RNN-based Seq2Seq model for generating mel spectrogram from text. The architecture is similar to that of Tacotron 2 BIBREF4 In the original Tacotron 2, the attention mechanism used was location sensitive attention BIBREF12 combined the original additive Seq2Seq BIBREF7 Bahdanau attention.

We propose to replace this attention with the simpler query-key attention from transformer model Following the logic above, we utilize a similar method from BIBREF6 that adds an additional guided attention loss to the overall loss objective, which acts to help the attention mechanism become monotoic as early as possible. As seen from FIGREF24 , an attention loss mask, INLINEFORM0 , is created applies a loss to force the attention alignment, INLINEFORM1 , to be nearly diagonal. 
 Question: Which modifications do they make to well-established Seq2seq architectures?

Replacing attention mechanism to query-key attention, and adding a loss to make the attention mask as diagonal as possible