Here there are the model, variables, folders and path creation and the extension conversion list

Model_Variables_Folders_ConversionList.py

# Import the Wav2Vec model and processor
model = "facebook/wav2vec2-base-960h"
print("Loading model: ", model)
processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")

#VARIABLES
path_base = "Audio files/"                      #Original speech/audio files folder
sr = 16000                                  #Sampling rate
block_length = 30                            #Speech chunk size
language = "en"               
expertai_account = "your_expert.ai_email"    #Your expert.ai email account
expertai_psw = "your_expert.ai_psw"                    #Your expert.ai psw
os.environ["EAI_USERNAME"] = expertai_account
os.environ["EAI_PASSWORD"] = expertai_psw

#Folders and Path Creation
audio_report = "Reports"                                  #This is the folder where your report will be stored
path_converted_audio = "converted_files/"                      #This is the temporary folder for converted audio files
resampled_folder = "resampled_files/"                          #This is the folder for the resampled audio files
Path(audio_report).mkdir(parents = True, exist_ok = True)           #This creates the reports folder
Path(path_converted_audio).mkdir(parents = True, exist_ok = True)   #This creates the folder for converted audio files
Path(resampled_folder).mkdir(parents = True, exist_ok = True)       #This creates the folder for resampled audio files

#Conversion List
extension_to_convert = ['.mp3','.mp4','.m4a','.flac','.opus']       #List of the supported files types/extensions