Upload app.py

app.py

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+import gradio as gr
+import torch
+import librosa
+import json
+from transformers import pipeline
+from stitched_model import CombinedModel
+
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+model = CombinedModel("ak3ra/wav2vec2-sunbird-speech-lug", "Sunbird/sunbird-mul-en-mbart-merged", device="cpu")
+
+
+def transcribe(audio_file_mic=None, audio_file_upload=None):
+    if audio_file_mic:
+        audio_file = audio_file_mic
+    elif audio_file_upload:
+        audio_file = audio_file_upload
+    else:
+        return "Please upload an audio file or record one"
+
+    # Make sure audio is 16kHz
+    speech, sample_rate = librosa.load(audio_file)
+    if sample_rate != 16000:
+        speech = librosa.resample(speech, orig_sr=sample_rate, target_sr=16000)
+    speech = torch.tensor([speech])
+
+    with torch.no_grad():
+        transcription, translation = model({"audio":speech})
+    
+    return transcription, translation[0]
+
+description = '''Luganda to English Speech Translation'''
+
+iface = gr.Interface(fn=transcribe,
+                     inputs=[
+                         gr.Audio(source="microphone", type="filepath", label="Record Audio"),
+                         gr.Audio(source="upload", type="filepath", label="Upload Audio")],
+                     outputs=[gr.Textbox(label="Transcription"),
+                              gr.Textbox(label="Translation")
+                     ],
+                     description=description
+                     )
+iface.launch()