Update app.py

app.py

@@ -1,35 +1,45 @@
 import numpy as np
+import torch
 import gradio as gr
-from transformers import Wav2Vec2ForCTC,Wav2Vec2Processor
+import torchaudio
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
 
+# Load ASR model & processor
 asr_model_id = "Norphel/wav2vec2-large-mms-1b-dzo-colab"
-asr_model = Wav2Vec2ForCTC.from_pretrained(asr_model_id, target_lang="dzo")
+asr_model = Wav2Vec2ForCTC.from_pretrained(asr_model_id, target_lang="dzo").to("cuda")
 asr_processor = Wav2Vec2Processor.from_pretrained(asr_model_id)
 asr_processor.tokenizer.set_target_lang("dzo")
 
+# Function to process audio & generate text
 def generate_text(audio):
-    sr, data = audio
-    print(data)
-    input_dict = asr_processor(aud_arr, sampling_rate=16_000, return_tensors="pt", padding=True)
-    logits = asr_model(input_dict.input_values.to("cuda")).logits
+    if audio is None:
+        return "No audio recorded."
+
+    sr, data = audio  # Gradio provides (sample_rate, waveform)
+    
+    # Resample to 16kHz if needed
+    if sr != 16000:
+        data = torchaudio.transforms.Resample(orig_freq=sr, new_freq=16000)(torch.tensor(data))
+
+    # Convert to model input format
+    input_dict = asr_processor(data.numpy(), sampling_rate=16000, return_tensors="pt", padding=True)
+    
+    # Run model inference
+    with torch.no_grad():
+        logits = asr_model(input_dict.input_values.to("cuda")).logits
     pred_ids = torch.argmax(logits, dim=-1)[0]
 
+    # Decode prediction
     return asr_processor.decode(pred_ids)
 
-input_audio = gr.Audio(
-    sources=["microphone"],
-    waveform_options=gr.WaveformOptions(
-        waveform_color="#01C6FF",
-        waveform_progress_color="#0066B4",
-        skip_length=2,
-        show_controls=False,
-    ),
-)
+# Gradio interface
 demo = gr.Interface(
     fn=generate_text,
-    inputs=input_audio,
-    outputs="text"
+    inputs=gr.Audio(type="numpy"),  # Automatically enables recording
+    outputs="text",
+    title="Dzongkha Speech-to-Text",
+    description="Record your voice and get transcriptions in Dzongkha."
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()