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https://github.com/kingridda/voice-cloning-AI.git
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adding the notebook
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kingridda
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sample_0.mp3
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sample_0.mp3
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voice cloning AI.ipynb
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voice cloning AI.ipynb
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"name": "voice_generator_AI.ipynb",
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"provenance": [],
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"collapsed_sections": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "code",
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"metadata": {
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"id": "lbdT4692nk7G"
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},
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"source": [
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"%tensorflow_version 1.x\n",
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"import os\n",
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"from os.path import join\n",
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"\n",
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"# Getting the model (PS: this is a famous but not official model)\n",
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"!git clone https://github.com/CorentinJ/Real-Time-Voice-Cloning.git\n",
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"project_name = 'Real-Time-Voice-Cloning'\n",
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"\n",
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"#Install requirements with some utils\n",
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"!cd {project_name} && pip install -q -r requirements.txt\n",
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"!apt-get install -qq libportaudio2\n",
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"!pip install -q https://github.com/tugstugi/dl-colab-notebooks/archive/colab_utils.zip\n",
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"\n",
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"#downloading pretrained weights\n",
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"!cd {project_name} && wget https://github.com/blue-fish/Real-Time-Voice-Cloning/releases/download/v1.0/pretrained.zip && unzip -o pretrained.zip"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "34S28kEKnx3t"
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},
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"source": [
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"#packages\n",
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"import sys\n",
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"sys.path.append(project_name)\n",
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"\n",
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"from IPython.display import display, Audio, clear_output\n",
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"from IPython.utils import io\n",
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"import ipywidgets as widgets\n",
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"import numpy as np\n",
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"from dl_colab_notebooks.audio import record_audio, upload_audio\n",
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"\n",
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"from synthesizer.inference import Synthesizer\n",
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"from encoder import inference as encoder\n",
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"from vocoder import inference as vocoder\n",
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"from pathlib import Path\n",
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"\n",
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"#loading weights to the models\n",
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"encoder.load_model(project_name / Path(\"encoder/saved_models/pretrained.pt\"))\n",
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"synthesizer = Synthesizer(project_name / Path(\"synthesizer/saved_models/pretrained/pretrained.pt\"))\n",
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"vocoder.load_model(project_name / Path(\"vocoder/saved_models/pretrained/pretrained.pt\"))"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "YYfgVfeX3zkU"
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},
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"source": [
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"#params (changes these as you please :)\n",
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"record_seconds = 10 # Record duration 1-10 seconds\n",
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"record_or_upload = \"Upload\" # fill this with Record (record now) or Upload (upload an audio)\n",
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"\n",
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"\n",
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"SAMPLE_RATE = 22050\n",
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"embedding = None\n",
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"def _compute_embedding(audio):\n",
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" display(Audio(audio, rate=SAMPLE_RATE, autoplay=True))\n",
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" global embedding\n",
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" embedding = None\n",
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" embedding = encoder.embed_utterance(encoder.preprocess_wav(audio, SAMPLE_RATE))\n",
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"def _record_audio(b):\n",
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" clear_output()\n",
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" audio = record_audio(record_seconds, sample_rate=SAMPLE_RATE)\n",
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" _compute_embedding(audio)\n",
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"def _upload_audio(b):\n",
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" clear_output()\n",
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" audio = upload_audio(sample_rate=SAMPLE_RATE)\n",
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" _compute_embedding(audio)\n",
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"\n",
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"if record_or_upload == \"Record\":\n",
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" button = widgets.Button(description=\"Record Your Voice\")\n",
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" button.on_click(_record_audio)\n",
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" display(button)\n",
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"else:\n",
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" _upload_audio(\"\")"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "BOV8CvVL4fl-"
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},
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"source": [
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"# text to output ( Please dont use this to generate something that is going to get you in trouble :'( )\n",
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"text = \"Hi people check this out this man Rida is doing something fun\" # text to say\n",
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"\n",
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"\n",
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"if embedding is None:\n",
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" print(\"first record or upload a voice file!\")\n",
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"else:\n",
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" print(\"Synthesizing new audio...\")\n",
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" #with io.capture_output() as captured:\n",
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" specs = synthesizer.synthesize_spectrograms([text], [embedding])\n",
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" generated_wav = vocoder.infer_waveform(specs[0])\n",
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" generated_wav = np.pad(generated_wav, (0, synthesizer.sample_rate), mode=\"constant\")\n",
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" clear_output()\n",
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" out_audio = Audio(generated_wav, rate=synthesizer.sample_rate, autoplay=True)\n",
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" display(out_audio)"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "aAhgj6Z_YixE"
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},
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"source": [
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"# download output audio file ( Please dont use this to generate something that is going to get you in trouble :'( )\n",
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"with open('out.wav', 'wb') as f:\n",
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" f.write(out_audio.data)"
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],
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"execution_count": null,
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"outputs": []
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}
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]
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}
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