Update asr.py

asr.py

@@ -5,20 +5,15 @@ 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 file_upload else microphone
-    if audio_fp is None:
+def transcribe(audio):
+    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]
-
-    # Set Faroese language
-    processor.tokenizer.set_target_lang("fao")
-    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")
 
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -27,7 +22,8 @@ def transcribe(audio_source=None, microphone=None, file_upload=None):
 
     with torch.no_grad():
         outputs = model(**inputs).logits
-        ids = torch.argmax(outputs, dim=-1)[0]
-        transcription = processor.decode(ids)
 
+    ids = torch.argmax(outputs, dim=-1)[0]
+    transcription = processor.decode(ids)
+    
     return transcription