Update asr.py

asr.py

@@ -3,23 +3,19 @@ from transformers import Wav2Vec2ForCTC, AutoProcessor
 import torch
 
 ASR_SAMPLING_RATE = 16_000
+
 MODEL_ID = "facebook/mms-1b-all"
 
 processor = AutoProcessor.from_pretrained(MODEL_ID)
 model = Wav2Vec2ForCTC.from_pretrained(MODEL_ID)
 
-def transcribe(audio_source=None, microphone=None, file_upload=None):
-    audio_fp = file_upload if "upload" in str(audio_source or "").lower() else microphone
-    if audio_fp is None:
+def transcribe(audio=None):
+    if audio is None:
         return "ERROR: You have to either use the microphone or upload an audio file"
     
-    audio_samples = librosa.load(audio_fp, sr=ASR_SAMPLING_RATE, mono=True)[0]
-    processor.tokenizer.set_target_lang("fao")  # Set Faroese language
-    model.load_adapter("fao")
-
+    audio_samples = librosa.load(audio, sr=ASR_SAMPLING_RATE, mono=True)[0]
     inputs = processor(audio_samples, sampling_rate=ASR_SAMPLING_RATE, return_tensors="pt")
 
-    # Set device
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     model.to(device)
     inputs = inputs.to(device)
@@ -29,5 +25,5 @@ def transcribe(audio_source=None, microphone=None, file_upload=None):
 
     ids = torch.argmax(outputs, dim=-1)[0]
     transcription = processor.decode(ids)
-
+    
     return transcription