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import speech_recognition as sr |
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from pydub import AudioSegment |
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import soundfile |
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import pyrebase |
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from pydub import AudioSegment |
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import soundfile |
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import os |
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import pyrebase |
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import gradio as gr |
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from transformers import AutoProcessor |
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from transformers import Wav2Vec2ForCTC |
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import gradio as gr |
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import torch |
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import torchaudio |
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from transformers import pipeline |
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classifier = pipeline("audio-classification", model="omarelsayeed/ed8am_elnoon_weltanween_bel8onna") |
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def recite_wav(path_name): |
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return classifier(path_name) |
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def list_all_files(): |
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for _file in storage.child("wavfiles").list_files(): |
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print(_file.name) |
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def download_wav_file(wav_name): |
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storage.child("wavfiles").child(wav_name).download("xd.wav") |
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def get_quran_text(wav_file_path): |
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download_wav_file(wav_file_path) |
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recitation = recite_wav("xd.wav") |
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os.remove("xd.wav") |
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return recitation |
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firebaseConfig = { |
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"apiKey": "AIzaSyDjgBD762KveE8GBO7jqTTkj_mKhUTDwGM", |
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"authDomain": "quran-c5cbe.firebaseapp.com", |
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"databaseURL":"quran-c5cbe.firebaseio.com/", |
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"projectId": "quran-c5cbe", |
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"storageBucket": "quran-c5cbe.appspot.com", |
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"serviceAccount":"quran-c5cbe-firebase-adminsdk-jvpbe-cebaf5aaa6.json" |
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} |
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firebase = pyrebase.initialize_app(firebaseConfig) |
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storage = firebase.storage() |
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iface = gr.Interface(fn=get_quran_text, inputs="text", outputs="text") |
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iface.launch() |
