diff --git a/chatterbot/chatterbot.py b/chatterbot/chatterbot.py
index c12bc7563..2a5049dff 100644
--- a/chatterbot/chatterbot.py
+++ b/chatterbot/chatterbot.py
@@ -160,6 +160,9 @@ def set_trainer(self, training_class, **kwargs):
 
         :param \**kwargs: Any parameters that should be passed to the training class.
         """
+        if 'chatbot' not in kwargs:
+            kwargs['chatbot'] = self
+
         self.trainer = training_class(self.storage, **kwargs)
 
     @property
diff --git a/chatterbot/trainers.py b/chatterbot/trainers.py
index 0a4b59a1f..beec74b58 100644
--- a/chatterbot/trainers.py
+++ b/chatterbot/trainers.py
@@ -2,7 +2,7 @@
 import os
 import sys
 from .conversation import Statement, Response
-from .utils import print_progress_bar
+from . import utils
 
 
 class Trainer(object):
@@ -11,12 +11,27 @@ class Trainer(object):
     """
 
     def __init__(self, storage, **kwargs):
+        self.chatbot = kwargs.get('chatbot')
         self.storage = storage
         self.logger = logging.getLogger(__name__)
 
+    def get_preprocessed_statement(self, input_statement):
+        """
+        Preprocess the input statement.
+        """
+
+        # The chatbot is optional to prevent backwards-incompatible changes
+        if not self.chatbot:
+            return input_statement
+
+        for preprocessor in self.chatbot.preprocessors:
+            input_statement = preprocessor(self, input_statement)
+
+        return input_statement
+
     def train(self, *args, **kwargs):
         """
-        This class must be overridden by a class the inherits from 'Trainer'.
+        This method must be overridden by a child class.
         """
         raise self.TrainerInitializationException()
 
@@ -25,10 +40,14 @@ def get_or_create(self, statement_text):
         Return a statement if it exists.
         Create and return the statement if it does not exist.
         """
-        statement = self.storage.find(statement_text)
+        temp_statement = self.get_preprocessed_statement(
+            Statement(text=statement_text)
+        )
+
+        statement = self.storage.find(temp_statement.text)
 
         if not statement:
-            statement = Statement(statement_text)
+            statement = Statement(temp_statement.text)
 
         return statement
 
@@ -81,7 +100,7 @@ def train(self, conversation):
         previous_statement_text = None
 
         for conversation_count, text in enumerate(conversation):
-            print_progress_bar("List Trainer", conversation_count + 1, len(conversation))
+            utils.print_progress_bar("List Trainer", conversation_count + 1, len(conversation))
 
             statement = self.get_or_create(text)
 
@@ -121,7 +140,7 @@ def train(self, *corpus_paths):
             corpus_files = self.corpus.list_corpus_files(corpus_path)
             for corpus_count, corpus in enumerate(corpora):
                 for conversation_count, conversation in enumerate(corpus):
-                    print_progress_bar(
+                    utils.print_progress_bar(
                         str(os.path.basename(corpus_files[corpus_count])) + " Training",
                         conversation_count + 1,
                         len(corpus)
diff --git a/tests/training_tests/test_training_preprocessors.py b/tests/training_tests/test_training_preprocessors.py
new file mode 100644
index 000000000..55888d1c4
--- /dev/null
+++ b/tests/training_tests/test_training_preprocessors.py
@@ -0,0 +1,30 @@
+from tests.base_case import ChatBotTestCase
+from chatterbot import trainers
+from chatterbot import preprocessors
+
+
+class PreprocessorTrainingTests(ChatBotTestCase):
+    """
+    These tests are designed to ensure that preprocessors
+    will be used to process the input the chat bot is given
+    during the training process.
+    """
+
+    def test_training_cleans_whitespace(self):
+        """
+        Test that the ``clean_whitespace`` preprocessor is used during
+        the training process.
+        """
+        self.chatbot.preprocessors = [preprocessors.clean_whitespace]
+        self.chatbot.set_trainer(trainers.ListTrainer)
+
+        self.chatbot.train([
+            'Can I help you with anything?',
+            'No, I     think I am all set.',
+            'Okay, have a nice day.',
+            'Thank you, you too.'
+        ])
+
+        response = self.chatbot.get_response('Can I help you with anything?')
+
+        self.assertEqual(response.text, 'No, I think I am all set.')