Fix test typos - audio feature extractors (#23310)

tests/models/mctct/test_feature_extraction_mctct.py

@@ -114,8 +114,8 @@ class MCTCTFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Te
     def test_call(self):
         # Tests that all call wrap to encode_plus and batch_encode_plus
         feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict())
-        # create three inputs of length 800, 1000, and 12000
-        speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 2000)]
+        # create three inputs of length 800, 1000, and 1200
+        speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
         np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
 
         # Test feature size

tests/models/speecht5/test_feature_extraction_speecht5.py

@@ -255,8 +255,8 @@ class SpeechT5FeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest
     def test_call_target(self):
         # Tests that all call wrap to encode_plus and batch_encode_plus
         feature_extractor = self.feature_extraction_class(**self.feat_extract_tester.prepare_feat_extract_dict())
-        # create three inputs of length 8000, 14000, and 2000
-        speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 2000)]
+        # create three inputs of length 800, 1000, and 1200
+        speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
         np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
 
         # Test feature size

tests/models/tvlt/test_feature_extraction_tvlt.py

@@ -160,7 +160,7 @@ class TvltFeatureExtractionTest(SequenceFeatureExtractionTestMixin, unittest.Tes
         feature_extractor = self.feature_extraction_class(**self.feat_extract_dict)
 
         # create three inputs of length 800, 1000, and 1200
-        speech_inputs = [floats_list((1, x))[0] for x in range(8000, 14000, 20000)]
+        speech_inputs = [floats_list((1, x))[0] for x in range(800, 1400, 200)]
         np_speech_inputs = [np.asarray(speech_input) for speech_input in speech_inputs]
 
         # Test not batched input