Papers with partitioning task

1 papers
Automatic Partitioning of a Code-Switched Speech Corpus Using Mixed-Integer Programming (2024.lrec-main)

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Challenge: Currently, partitioning speech corpora is done by hand, but this is not feasible for the dataset under investigation.
Approach: They propose to partition a 41.6-hour corpus of code-switched speech into training, development and testing partitions using mixed-integer linear programming.
Outcome: The proposed method allows to partition a 41.6-hour corpus of code-switched speech into training, development and testing partitions while maintaining a fixed number of speakers and a specific amount of codeswitching speech in the development and test partitions.

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