Fix some Wav2Vec2 related models' doctest (#27462)

* fix

* fix

* fix

* fix

* fix

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

src/transformers/models/wav2vec2/tokenization_wav2vec2.py

@@ -603,7 +603,7 @@ class Wav2Vec2CTCTokenizer(PreTrainedTokenizer):
         >>> feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h")
 
         >>> # load first sample of English common_voice
-        >>> dataset = load_dataset("common_voice", "en", split="train", streaming=True)
+        >>> dataset = load_dataset("mozilla-foundation/common_voice_11_0", "en", split="train", streaming=True)
         >>> dataset = dataset.cast_column("audio", datasets.Audio(sampling_rate=16_000))
         >>> dataset_iter = iter(dataset)
         >>> sample = next(dataset_iter)
@@ -626,10 +626,10 @@ class Wav2Vec2CTCTokenizer(PreTrainedTokenizer):
         ...     }
         ...     for d in outputs.word_offsets
         ... ]
-        >>> # compare word offsets with audio `common_voice_en_100038.mp3` online on the dataset viewer:
-        >>> # https://huggingface.co/datasets/common_voice/viewer/en/train
+        >>> # compare word offsets with audio `en_train_0/common_voice_en_19121553.mp3` online on the dataset viewer:
+        >>> # https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/en
         >>> word_offsets[:3]
-        [{'word': 'WHY', 'start_time': 1.42, 'end_time': 1.54}, {'word': 'DOES', 'start_time': 1.64, 'end_time': 1.9}, {'word': 'MILISANDRA', 'start_time': 2.26, 'end_time': 2.9}]
+        [{'word': 'THE', 'start_time': 0.7, 'end_time': 0.78}, {'word': 'TRICK', 'start_time': 0.88, 'end_time': 1.08}, {'word': 'APPEARS', 'start_time': 1.2, 'end_time': 1.64}]
         ```"""
         # Convert inputs to python lists
         token_ids = to_py_obj(token_ids)

src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py

@@ -538,7 +538,7 @@ class Wav2Vec2ProcessorWithLM(ProcessorMixin):
         >>> processor = AutoProcessor.from_pretrained("patrickvonplaten/wav2vec2-base-100h-with-lm")
 
         >>> # load first sample of English common_voice
-        >>> dataset = load_dataset("common_voice", "en", split="train", streaming=True)
+        >>> dataset = load_dataset("mozilla-foundation/common_voice_11_0", "en", split="train", streaming=True)
         >>> dataset = dataset.cast_column("audio", datasets.Audio(sampling_rate=16_000))
         >>> dataset_iter = iter(dataset)
         >>> sample = next(dataset_iter)
@@ -561,10 +561,10 @@ class Wav2Vec2ProcessorWithLM(ProcessorMixin):
         ...     }
         ...     for d in outputs.word_offsets
         ... ]
-        >>> # compare word offsets with audio `common_voice_en_100038.mp3` online on the dataset viewer:
-        >>> # https://huggingface.co/datasets/common_voice/viewer/en/train
+        >>> # compare word offsets with audio `en_train_0/common_voice_en_19121553.mp3` online on the dataset viewer:
+        >>> # https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/en
         >>> word_offsets[:4]
-        [{'word': 'WHY', 'start_time': 1.42, 'end_time': 1.54}, {'word': 'DOES', 'start_time': 1.66, 'end_time': 1.9}, {'word': 'MILISANDRA', 'start_time': 2.26, 'end_time': 2.9}, {'word': 'LOOK', 'start_time': 3.0, 'end_time': 3.16}]
+        [{'word': 'THE', 'start_time': 0.68, 'end_time': 0.78}, {'word': 'TRACK', 'start_time': 0.88, 'end_time': 1.1}, {'word': 'APPEARS', 'start_time': 1.18, 'end_time': 1.66}, {'word': 'ON', 'start_time': 1.86, 'end_time': 1.92}]
         ```"""
 
         from pyctcdecode.constants import (