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However, using a development dataset, these weights can be trained and later applied during evaluation.
Acoustic model parameters for both baseline and proposed methods are optimized using a development dataset.
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We use a development dataset containing 200 speech segments and 200 non-speech segments to choose the optimal feature subset.
Finally, 490 participants were included in this study, and the data from them were used as a development dataset.
The performance of a prognostic model derived using a development sample will also need to be externally validated using an independent dataset [ 1], but missing data within the development and or validation sample complicate these analyses.
To avoid this problem in practice, a development dataset needs to be used to tune and determine an appropriate configuration before each implementation.
We trained our detecting, tracking, and recognition algorithm using 100 hours of a development dataset.
Each dataset acts as a development dataset.
The datasets were divided randomly into a development dataset and a test dataset.
Options like cut-off threshold and number of quantized brackets for acoustic features are also optimally tuned using the development dataset.
A multivariate logistic regression analysis including variables mentioned above was performed to predict in-hospital mortality using the development dataset.
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