Update README.md

README.md

@@ -81,10 +81,6 @@ print("Reference:", test_dataset["sentence"][:2])
 The model can be evaluated as follows on the Japanese test data of Common Voice.
 
 ```python
-!pip install mecab-python3
-!pip install unidic-lite
-!python -m unidic download
-
 import torch
 import torchaudio
 from datasets import load_dataset, load_metric
@@ -98,7 +94,7 @@ processor = Wav2Vec2Processor.from_pretrained("qqhann/w2v_hf_jsut_xlsr53")
 model = Wav2Vec2ForCTC.from_pretrained("qqhann/w2v_hf_jsut_xlsr53")
 model.to("cuda")
 
-chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“]'  # TODO: adapt this list to include all special characters you removed from the data
+chars_to_ignore_regex = '[\\\\,\\\\?\\\\.\\\\!\\\\-\\\\;\\\\:\\\\"\\\\“]'  # TODO: adapt this list to include all special characters you removed from the data
 # resampler = torchaudio.transforms.Resample(48_000, 16_000) # JSUT is already 16kHz
 resampler = torchaudio.transforms.Resample(16_000, 16_000) # JSUT is already 16kHz