text: Title: [Feature]: Class-dependent label noise simulation
  Body: ### Problem statement
  
  Currently Flair allows to generate only uniform label noise, which does not account for any similarities between the data points in the dataset. Generating class-dependent label noise would allow for a more realistic scenario, in which models have to deal with labelling mistakes/inaccuracies.
  
  ### Solution
  
  Extend the `_corrupt_labels()` method of the `Corpus` by allowing to pass a pre-defined noise transition matrix.
  
  ### Additional Context
  
  _No response_