Delete app.py

app.py

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-# -*- coding: utf-8 -*-
-"""AI_Club_Multilingual_Speech_Synthesis_Friday.ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1EZPulIF2l2emrtMxVSm4q9D__aWLmpp-
-
-# AI Club Multilingual Speech Synthesis
-Spring 2024 AI Club at San Diego State University
-
-## Downloading library dependencies
-"""
-pip install --upgrade pip
-pip install spacy
-pip install gradio
-pip install git+https://github.com/openai/whisper.git
-pip install translate
-pip install TTS
-
-"""## Importing libraries and dependencies"""
-
-import gradio as gr
-import numpy as np
-#import ffmpeg
-import whisper
-from translate import Translator
-from TTS.api import TTS
-
-# Loading the base model
-model = whisper.load_model("base")
-
-def speech_to_text(audio):
-    result = model.transcribe(audio)
-    return result["text"] # Only first tuple
-
-# Defining the Translate Function
-def translate(text, language):
-    # Replace this with actual translation logic using a translation library or API
-    translator = Translator(to_lang=language)
-    translated_text = translator.translate(text)
-    return translated_text
-
-# Initialize TTS model outside the function to avoid reinitialization on each call
-tts_model = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=True)
-
-# Speech to Speech Function
-def s2s(audio, language):
-    # Do some text processing here (transcription and translation)
-    result_text = speech_to_text(audio)
-    translated_text = translate(result_text, language)
-
-    # Generate speech using the input audio as the speaker's voice
-    tts_model.tts_to_file(text=translated_text,
-                          file_path="output.wav",
-                          speaker_wav=audio,
-                          language=language)
-    with open("output.wav", "rb") as audio_file:
-        audio_data = audio_file.read()
-
-    return [result_text, translated_text, audio_data]
-
-# List of supported language codes
-language_names = ["Arabic", "Portuguese", "Chinese", "Czech", "Dutch",
-                  "English", "French", "German", "Italian", "Polish",
-                  "Russian", "Spanish", "Turkish", "Korean",
-                  "Hungarian", "Hindi"]
-language_options = ["ar",
-                    "pt",
-                    "zh-cn",
-                    "cs",
-                    "nl",
-                    "en",
-                    "fr",
-                    "de",
-                    "it",
-                    "pl",
-                    "ru",
-                    "es",
-                    "tr",
-                    "ko",
-                    "hu",
-                    "hi"]
-
-language_dropdown = gr.Dropdown(choices = zip(language_names, language_options),
-                                value= "es",
-                                label="Target Language",
-)
-
-translate_button = gr.Button(value="Synthesize and Translate my Voice!")
-transcribed_text = gr.Textbox(label="Transcribed Text")
-output_text = gr.Textbox(label="Translated Text")
-output_speech = gr.Audio(label="Translated Speech", type="filepath")
-
-# Gradio interface with the transcribe function as the main function
-demo = gr.Interface(
-    # title='Speech Translation',
-    fn=s2s,
-    inputs=[gr.Audio(sources=["upload", "microphone"],
-                     type="filepath", format = "wav",
-                     show_download_button=True,
-                     waveform_options=gr.WaveformOptions(
-                        waveform_color="#01C6FF",
-                        waveform_progress_color="#0066B4",
-                        skip_length=2,
-                        show_controls=False,
-                        )
-                     ),
-            language_dropdown],
-    outputs=[transcribed_text, output_text, output_speech],
-
-    title="Speech-to-Speech Translation (Demo)"
-)
-#demo.launch(debug=True, share = True)
-demo.launch()