diff --git a/delta/corpus.py b/delta/corpus.py
index 5f1dcce..5bc00fb 100644
--- a/delta/corpus.py
+++ b/delta/corpus.py
@@ -10,6 +10,7 @@ class which represents the feature matrix. Also contained are default
 import os
 import glob
 from fnmatch import fnmatch
+from inspect import signature
 from typing import Type
 
 import regex as re
@@ -254,7 +255,7 @@ class Corpus(pd.DataFrame):
     _metadata = ['metadata']
 
     def __init__(self, subdir=None, file=None, corpus=None,
-                 feature_generator=FeatureGenerator(),
+                 feature_generator=None,
                  document_describer=DefaultDocumentDescriber(),
                  metadata=None, **kwargs):
         """
@@ -264,9 +265,11 @@ def __init__(self, subdir=None, file=None, corpus=None,
             subdir (str): Path to a subdirectory containing the (unprocessed) corpus data.
             file (str): Path to a CSV file containing the feature vectors.
             corpus (pandas.DataFrame): A dataframe or :class:`Corpus` from which to create a new corpus, as a copy.
-            feature_generator (FeatureGenerator): A customizeable helper class that will process a `subdir` to a feature matrix, if the `subdir` argument is also given.
+            feature_generator (FeatureGenerator): A customizeable helper class that will process a `subdir` to a feature matrix, if the `subdir` argument is also given. If None, a default feature generator will be used.
             metadata (dict): A dictionary with metadata to copy into the new corpus.
-            **kwargs: Additional keyword arguments will be set in the metadata record of the new corpus.
+            **kwargs: Additionally, if feature_generator is None and subdir is not None, you can pass FeatureGenerator
+                arguments and they will be used when instantiating the feature generator
+                Additional keyword arguments will be set in the metadata record of the new corpus.
         """
         logger = logging.getLogger(__name__)
 
@@ -290,6 +293,15 @@ def __init__(self, subdir=None, file=None, corpus=None,
 
         # initialize data
         if subdir is not None:
+            if feature_generator is None:
+                fg_sig_arguments = signature(FeatureGenerator).parameters
+                fg_actual_args = {}
+                for key, value in kwargs.copy().items():
+                    if key in fg_sig_arguments:
+                        fg_actual_args[key] = value
+                        del kwargs[key]
+                feature_generator = FeatureGenerator(**fg_actual_args)
+
             logger.info(
                 "Creating corpus by reading %s using %s",
                 subdir,
diff --git a/test/corpus_test.py b/test/corpus_test.py
index d28ec2b..50a6e6c 100644
--- a/test/corpus_test.py
+++ b/test/corpus_test.py
@@ -69,3 +69,8 @@ def test_table_describer(testdir):
     corpus = d.Corpus(testdir,
                       document_describer=d.util.TableDocumentDescriber(testdir + '.csv', 'Author', 'Title'))
     assert corpus.document_describer.group_name(corpus.index[-1]) in {'Raabe', 'Marlitt', 'Fontane'}
+
+
+def test_featuredescriber_args(testdir):
+    corpus = d.Corpus(testdir, lower_case=True)
+    assert 'Sie' not in corpus.columns
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