diff --git a/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py b/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
index c31b209c1879..2dc88564bf86 100644
--- a/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
+++ b/src/transformers/models/wav2vec2_with_lm/processing_wav2vec2_with_lm.py
@@ -42,9 +42,15 @@ class Wav2Vec2DecoderWithLMOutput(ModelOutput):
     Args:
         text (list of `str`):
             Decoded logits in text from. Usually the speech transcription.
+        logit_score (list of `float`):
+            Total logit score of the beam associated with produced text.
+        lm_score (list of `float`):
+            Fused lm_score of the beam associated with produced text.
     """
 
     text: Union[List[str], str]
+    logit_score: Union[List[float], float] = None
+    lm_score: Union[List[float], float] = None
 
 
 class Wav2Vec2ProcessorWithLM(ProcessorMixin):
@@ -283,7 +289,8 @@ def batch_decode(
         )
 
         # create multiprocessing pool and list numpy arrays
-        logits_list = [array for array in logits]
+        # filter out logits padding
+        logits_list = [array[(array != -100.0).all(axis=-1)] for array in logits]
         pool = get_context("fork").Pool(num_processes)
 
         # pyctcdecode
@@ -300,11 +307,14 @@ def batch_decode(
         # clone multi-processing pool
         pool.close()
 
-        # extract text
-        batch_texts = [d[0][0] for d in decoded_beams]
-
+        # extract text and scores
+        batch_texts, logit_scores, lm_scores = [], [], []
+        for d in decoded_beams:
+            batch_texts.append(d[0][0])
+            logit_scores.append(d[0][-2])
+            lm_scores.append(d[0][-1])
         # more output features will be added in the future
-        return Wav2Vec2DecoderWithLMOutput(text=batch_texts)
+        return Wav2Vec2DecoderWithLMOutput(text=batch_texts, logit_score=logit_scores, lm_score=lm_scores)
 
     def decode(
         self,
@@ -379,7 +389,9 @@ def decode(
         )
 
         # more output features will be added in the future
-        return Wav2Vec2DecoderWithLMOutput(text=decoded_beams[0][0])
+        return Wav2Vec2DecoderWithLMOutput(
+            text=decoded_beams[0][0], logit_score=decoded_beams[0][-2], lm_score=decoded_beams[0][-1]
+        )
 
     @contextmanager
     def as_target_processor(self):
diff --git a/tests/test_processor_wav2vec2_with_lm.py b/tests/test_processor_wav2vec2_with_lm.py
index f918a0894a47..800e4cbdc735 100644
--- a/tests/test_processor_wav2vec2_with_lm.py
+++ b/tests/test_processor_wav2vec2_with_lm.py
@@ -177,12 +177,14 @@ def test_decoder(self):
 
         logits = self._get_dummy_logits(shape=(10, 16), seed=13)
 
-        decoded_processor = processor.decode(logits).text
+        decoded_processor = processor.decode(logits)
 
-        decoded_decoder = decoder.decode_beams(logits)[0][0]
+        decoded_decoder = decoder.decode_beams(logits)[0]
 
-        self.assertEqual(decoded_decoder, decoded_processor)
-        self.assertEqual("</s> <s> </s>", decoded_processor)
+        self.assertEqual(decoded_decoder[0], decoded_processor.text)
+        self.assertEqual("</s> <s> </s>", decoded_processor.text)
+        self.assertEqual(decoded_decoder[-2], decoded_processor.logit_score)
+        self.assertEqual(decoded_decoder[-1], decoded_processor.lm_score)
 
     def test_decoder_batch(self):
         feature_extractor = self.get_feature_extractor()
@@ -193,15 +195,22 @@ def test_decoder_batch(self):
 
         logits = self._get_dummy_logits()
 
-        decoded_processor = processor.batch_decode(logits).text
+        decoded_processor = processor.batch_decode(logits)
 
         logits_list = [array for array in logits]
         pool = get_context("fork").Pool()
-        decoded_decoder = [d[0][0] for d in decoder.decode_beams_batch(pool, logits_list)]
+        decoded_beams = decoder.decode_beams_batch(pool, logits_list)
+        texts_decoder, logit_scores_decoder, lm_scores_decoder = [], [], []
+        for beams in decoded_beams:
+            texts_decoder.append(beams[0][0])
+            logit_scores_decoder.append(beams[0][-2])
+            lm_scores_decoder.append(beams[0][-1])
         pool.close()
 
-        self.assertListEqual(decoded_decoder, decoded_processor)
-        self.assertListEqual(["<s> <s> </s>", "<s> <s> <s>"], decoded_processor)
+        self.assertListEqual(texts_decoder, decoded_processor.text)
+        self.assertListEqual(["<s> <s> </s>", "<s> <s> <s>"], decoded_processor.text)
+        self.assertListEqual(logit_scores_decoder, decoded_processor.logit_score)
+        self.assertListEqual(lm_scores_decoder, decoded_processor.lm_score)
 
     def test_decoder_with_params(self):
         feature_extractor = self.get_feature_extractor()