app.py

# Imports
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import cross_val_predict
from sklearn.metrics import accuracy_score
import joblib
import os
import pandas as pd
import numpy as np
import random
import tensorflow as tf
import torch
from tqdm import tqdm
import tensorflow_io as tfio
from pathlib import Path
from IPython import display
from speechbrain.pretrained import EncoderClassifier
import torchaudio
import joblib



# Defining the transcription function
def snoring(audio):
    return text

# Defining the audio filepaths
audio = gr.inputs.Audio(type="filepath")

# Loading the gradio framwork
iface = gr.Interface(fn=snoring,inputs=audio, outputs="text", title="Snore.AI", description="Detect Snotring with artificial intelligence.")
iface.launch()