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Parent(s):
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Create multi
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| 1 |
+
{
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| 2 |
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"cells": [
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| 3 |
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{
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| 4 |
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"cell_type": "markdown",
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| 5 |
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"id": "b6ee1ede",
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| 6 |
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"metadata": {},
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| 7 |
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"source": [
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| 8 |
+
"## Cross-Lingual Voice Clone Demo"
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| 9 |
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]
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},
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| 11 |
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{
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"cell_type": "code",
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"execution_count": null,
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| 14 |
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"id": "b7f043ee",
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| 15 |
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"metadata": {},
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| 16 |
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"outputs": [],
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| 17 |
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"source": [
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| 18 |
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"import os\n",
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| 19 |
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"import torch\n",
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| 20 |
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"import se_extractor\n",
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"from api import ToneColorConverter"
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]
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},
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{
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"cell_type": "markdown",
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"id": "15116b59",
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| 27 |
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"metadata": {},
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| 28 |
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"source": [
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| 29 |
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"### Initialization"
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| 30 |
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]
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| 31 |
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},
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| 32 |
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{
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| 33 |
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"cell_type": "code",
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| 34 |
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"execution_count": null,
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| 35 |
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"id": "aacad912",
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| 36 |
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"metadata": {},
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| 37 |
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"outputs": [],
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| 38 |
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"source": [
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| 39 |
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"ckpt_converter = 'checkpoints/converter'\n",
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| 40 |
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"device = 'cuda:0'\n",
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| 41 |
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"output_dir = 'outputs'\n",
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| 42 |
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"\n",
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| 43 |
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"tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)\n",
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| 44 |
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"tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')\n",
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| 45 |
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"\n",
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| 46 |
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"os.makedirs(output_dir, exist_ok=True)"
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| 47 |
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]
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| 48 |
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},
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| 49 |
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{
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| 50 |
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"cell_type": "markdown",
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| 51 |
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"id": "3db80fcf",
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| 52 |
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"metadata": {},
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| 53 |
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"source": [
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| 54 |
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"In this demo, we will use OpenAI TTS as the base speaker to produce multi-lingual speech audio. The users can flexibly change the base speaker according to their own needs. Please create a file named `.env` and place OpenAI key as `OPENAI_API_KEY=xxx`. We have also provided a Chinese base speaker model (see `demo_part1.ipynb`)."
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| 55 |
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]
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| 56 |
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},
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| 57 |
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{
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| 58 |
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"cell_type": "code",
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| 59 |
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"execution_count": null,
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| 60 |
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"id": "3b245ca3",
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| 61 |
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"metadata": {},
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| 62 |
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"outputs": [],
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| 63 |
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"source": [
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| 64 |
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"from openai import OpenAI\n",
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| 65 |
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"from dotenv import load_dotenv\n",
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| 66 |
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"\n",
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| 67 |
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"# Please create a file named .env and place your\n",
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| 68 |
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"# OpenAI key as OPENAI_API_KEY=xxx\n",
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| 69 |
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"load_dotenv() \n",
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| 70 |
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"\n",
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| 71 |
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"client = OpenAI(api_key=os.environ.get(\"OPENAI_API_KEY\"))\n",
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| 72 |
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"\n",
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| 73 |
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"response = client.audio.speech.create(\n",
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| 74 |
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" model=\"tts-1\",\n",
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| 75 |
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" voice=\"nova\",\n",
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| 76 |
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" input=\"This audio will be used to extract the base speaker tone color embedding. \" + \\\n",
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| 77 |
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" \"Typically a very short audio should be sufficient, but increasing the audio \" + \\\n",
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| 78 |
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" \"length will also improve the output audio quality.\"\n",
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| 79 |
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")\n",
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| 80 |
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"\n",
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| 81 |
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"response.stream_to_file(f\"{output_dir}/openai_source_output.mp3\")"
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| 82 |
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]
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| 83 |
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},
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| 84 |
+
{
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| 85 |
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"cell_type": "markdown",
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| 86 |
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"id": "7f67740c",
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| 87 |
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"metadata": {},
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| 88 |
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"source": [
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| 89 |
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"### Obtain Tone Color Embedding"
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| 90 |
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]
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| 91 |
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},
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| 92 |
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{
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| 93 |
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"cell_type": "markdown",
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| 94 |
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"id": "f8add279",
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| 95 |
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"metadata": {},
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| 96 |
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"source": [
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| 97 |
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"The `source_se` is the tone color embedding of the base speaker. \n",
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| 98 |
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"It is an average for multiple sentences with multiple emotions\n",
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| 99 |
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"of the base speaker. We directly provide the result here but\n",
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| 100 |
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"the readers feel free to extract `source_se` by themselves."
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| 101 |
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]
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| 102 |
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},
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| 103 |
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{
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| 104 |
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"cell_type": "code",
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| 105 |
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"execution_count": null,
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| 106 |
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"id": "63ff6273",
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| 107 |
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"metadata": {},
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| 108 |
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"outputs": [],
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| 109 |
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"source": [
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| 110 |
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"base_speaker = f\"{output_dir}/openai_source_output.mp3\"\n",
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| 111 |
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"source_se, audio_name = se_extractor.get_se(base_speaker, tone_color_converter, vad=True)\n",
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| 112 |
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"\n",
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| 113 |
+
"reference_speaker = 'resources/example_reference.mp3'\n",
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| 114 |
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"target_se, audio_name = se_extractor.get_se(reference_speaker, tone_color_converter, vad=True)"
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| 115 |
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]
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| 116 |
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},
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| 117 |
+
{
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| 118 |
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"cell_type": "markdown",
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| 119 |
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"id": "a40284aa",
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| 120 |
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"metadata": {},
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| 121 |
+
"source": [
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| 122 |
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"### Inference"
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| 123 |
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]
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| 124 |
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},
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| 125 |
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{
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| 126 |
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"cell_type": "code",
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| 127 |
+
"execution_count": null,
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| 128 |
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"id": "73dc1259",
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| 129 |
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"metadata": {},
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| 130 |
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"outputs": [],
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| 131 |
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"source": [
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| 132 |
+
"# Run the base speaker tts\n",
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| 133 |
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"text = [\n",
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| 134 |
+
" \"MyShell is a decentralized and comprehensive platform for discovering, creating, and staking AI-native apps.\",\n",
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| 135 |
+
" \"MyShell es una plataforma descentralizada y completa para descubrir, crear y apostar por aplicaciones nativas de IA.\",\n",
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| 136 |
+
" \"MyShell est une plateforme décentralisée et complète pour découvrir, créer et miser sur des applications natives d'IA.\",\n",
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| 137 |
+
" \"MyShell ist eine dezentralisierte und umfassende Plattform zum Entdecken, Erstellen und Staken von KI-nativen Apps.\",\n",
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| 138 |
+
" \"MyShell è una piattaforma decentralizzata e completa per scoprire, creare e scommettere su app native di intelligenza artificiale.\",\n",
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| 139 |
+
" \"MyShellは、AIネイティブアプリの発見、作成、およびステーキングのための分散型かつ包括的なプラットフォームです。\",\n",
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| 140 |
+
" \"MyShell — это децентрализованная и всеобъемлющая платформа для обнаружения, создания и стейкинга AI-ориентированных приложений.\",\n",
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| 141 |
+
" \"MyShell هي منصة لامركزية وشاملة لاكتشاف وإنشاء ورهان تطبيقات الذكاء الاصطناعي الأصلية.\",\n",
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| 142 |
+
" \"MyShell是一个去中心化且全面的平台,用于发现、创建和投资AI原生应用程序。\",\n",
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| 143 |
+
" \"MyShell एक विकेंद्रीकृत और व्यापक मंच है, जो AI-मूल ऐप्स की खोज, सृजन और स्टेकिंग के लिए है।\",\n",
|
| 144 |
+
" \"MyShell é uma plataforma descentralizada e abrangente para descobrir, criar e apostar em aplicativos nativos de IA.\"\n",
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| 145 |
+
"]\n",
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| 146 |
+
"src_path = f'{output_dir}/tmp.wav'\n",
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| 147 |
+
"\n",
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| 148 |
+
"for i, t in enumerate(text):\n",
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| 149 |
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"\n",
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| 150 |
+
" response = client.audio.speech.create(\n",
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| 151 |
+
" model=\"tts-1\",\n",
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| 152 |
+
" voice=\"alloy\",\n",
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| 153 |
+
" input=t,\n",
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| 154 |
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" )\n",
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| 155 |
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"\n",
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| 156 |
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" response.stream_to_file(src_path)\n",
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| 157 |
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"\n",
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| 158 |
+
" save_path = f'{output_dir}/output_crosslingual_{i}.wav'\n",
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| 159 |
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"\n",
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| 160 |
+
" # Run the tone color converter\n",
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| 161 |
+
" encode_message = \"@MyShell\"\n",
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| 162 |
+
" tone_color_converter.convert(\n",
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| 163 |
+
" audio_src_path=src_path, \n",
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| 164 |
+
" src_se=source_se, \n",
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| 165 |
+
" tgt_se=target_se, \n",
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| 166 |
+
" output_path=save_path,\n",
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| 167 |
+
" message=encode_message)"
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| 168 |
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]
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| 169 |
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}
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| 170 |
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],
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| 171 |
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"metadata": {
|
| 172 |
+
"interpreter": {
|
| 173 |
+
"hash": "9d70c38e1c0b038dbdffdaa4f8bfa1f6767c43760905c87a9fbe7800d18c6c35"
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| 174 |
+
},
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| 175 |
+
"kernelspec": {
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| 176 |
+
"display_name": "Python 3.9.18 ('openvoice')",
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| 177 |
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"language": "python",
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| 178 |
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"name": "python3"
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| 179 |
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},
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| 180 |
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"language_info": {
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| 181 |
+
"codemirror_mode": {
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| 182 |
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"name": "ipython",
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| 183 |
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"version": 3
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| 184 |
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},
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| 185 |
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"file_extension": ".py",
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| 186 |
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"mimetype": "text/x-python",
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| 187 |
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"name": "python",
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| 188 |
+
"nbconvert_exporter": "python",
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| 189 |
+
"pygments_lexer": "ipython3",
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| 190 |
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"version": "3.9.18"
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| 191 |
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}
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| 192 |
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},
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| 193 |
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"nbformat": 4,
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| 194 |
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"nbformat_minor": 5
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| 195 |
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}
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