Update notebook
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@ -40,7 +40,8 @@
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"source": [
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"source": [
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"!git clone https://github.com/neonbjb/tortoise-tts.git\n",
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"!git clone https://github.com/neonbjb/tortoise-tts.git\n",
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"%cd tortoise-tts\n",
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"%cd tortoise-tts\n",
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"!pip install -r requirements.txt"
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"!pip3 install -r requirements.txt\n",
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"!python3 setup.py install"
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]
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]
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},
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},
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{
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{
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@ -54,8 +55,8 @@
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"\n",
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"\n",
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"import IPython\n",
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"import IPython\n",
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"\n",
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"\n",
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"from api import TextToSpeech\n",
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"from tortoise.api import TextToSpeech\n",
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"from utils.audio import load_audio, get_voices\n",
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"from tortoise.utils.audio import load_audio, load_voice, load_voices\n",
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"\n",
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"\n",
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"# This will download all the models used by Tortoise from the HF hub.\n",
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"# This will download all the models used by Tortoise from the HF hub.\n",
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"tts = TextToSpeech()"
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"tts = TextToSpeech()"
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@ -66,20 +67,6 @@
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"execution_count": null,
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"execution_count": null,
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"outputs": []
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"outputs": []
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},
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},
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{
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"cell_type": "code",
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"source": [
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"# List all the voices available. These are just some random clips I've gathered\n",
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"# from the internet as well as a few voices from the training dataset.\n",
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"# Feel free to add your own clips to the voices/ folder.\n",
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"%ls voices"
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],
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"metadata": {
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"id": "SSleVnRAiEE2"
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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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"cell_type": "code",
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"cell_type": "code",
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"source": [
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"source": [
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@ -94,8 +81,6 @@
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"Though as for that the passing there\n",
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"Though as for that the passing there\n",
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"Had worn them really about the same,\"\"\"\n",
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"Had worn them really about the same,\"\"\"\n",
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"\n",
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"\n",
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"# Pick one of the voices from above\n",
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"voice = 'train_dotrice'\n",
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"# Pick a \"preset mode\" to determine quality. Options: {\"ultra_fast\", \"fast\" (default), \"standard\", \"high_quality\"}. See docs in api.py\n",
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"# Pick a \"preset mode\" to determine quality. Options: {\"ultra_fast\", \"fast\" (default), \"standard\", \"high_quality\"}. See docs in api.py\n",
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"preset = \"fast\""
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"preset = \"fast\""
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],
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],
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@ -108,15 +93,32 @@
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"source": [
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"source": [
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"# Fetch the voice references and forward execute!\n",
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"# Tortoise will attempt to mimic voices you provide. It comes pre-packaged\n",
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"voices = get_voices()\n",
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"# with some voices you might recognize.\n",
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"cond_paths = voices[voice]\n",
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"conds = []\n",
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"for cond_path in cond_paths:\n",
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" c = load_audio(cond_path, 22050)\n",
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" conds.append(c)\n",
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"\n",
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"\n",
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"gen = tts.tts_with_preset(text, conds, preset)\n",
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"# Let's list all the voices available. These are just some random clips I've gathered\n",
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"# from the internet as well as a few voices from the training dataset.\n",
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"# Feel free to add your own clips to the voices/ folder.\n",
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"%ls tortoise/voices\n",
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"\n",
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"IPython.display.Audio('tortoise/voices/tom/1.wav')"
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],
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"metadata": {
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"id": "SSleVnRAiEE2"
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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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"source": [
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"# Pick one of the voices from the output above\n",
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"voice = 'tom'\n",
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"\n",
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"# Load it and send it through Tortoise.\n",
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"voice_samples, conditioning_latents = load_voice(voice)\n",
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"gen = tts.tts_with_preset(text, voice_samples=voice_samples, conditioning_latents=conditioning_latents, \n",
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" preset=preset)\n",
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"torchaudio.save('generated.wav', gen.squeeze(0).cpu(), 24000)\n",
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"torchaudio.save('generated.wav', gen.squeeze(0).cpu(), 24000)\n",
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"IPython.display.Audio('generated.wav')"
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"IPython.display.Audio('generated.wav')"
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],
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],
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@ -129,19 +131,29 @@
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"source": [
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"source": [
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"# You can add as many conditioning voices as you want together. Combining\n",
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"# Tortoise can also generate speech using a random voice. The voice changes each time you execute this!\n",
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"# clips from multiple voices takes the mean of the latent space for all\n",
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"# (Note: random voices can be prone to strange utterances)\n",
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"# voices. This creates a novel voice that is a combination of the two inputs.\n",
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"gen = tts.tts_with_preset(text, voice_samples=None, conditioning_latents=None, preset=preset)\n",
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"torchaudio.save('generated.wav', gen.squeeze(0).cpu(), 24000)\n",
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"IPython.display.Audio('generated.wav')"
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],
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"metadata": {
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"id": "16Xs2SSC3BXa"
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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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"source": [
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"# You can also combine conditioning voices. Combining voices produces a new voice\n",
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"# with traits from all the parents.\n",
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"#\n",
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"#\n",
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"# Lets see what it would sound like if Picard and Kirk had a kid with a penchant for philosophy:\n",
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"# Lets see what it would sound like if Picard and Kirk had a kid with a penchant for philosophy:\n",
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"conds = []\n",
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"voice_samples, conditioning_latents = load_voices(['pat', 'william'])\n",
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"for v in ['pat', 'william']:\n",
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" cond_paths = voices[v]\n",
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" for cond_path in cond_paths:\n",
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" c = load_audio(cond_path, 22050)\n",
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" conds.append(c)\n",
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"\n",
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"\n",
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"gen = tts.tts_with_preset(\"They used to say that if man was meant to fly, he’d have wings. But he did fly. He discovered he had to.\", conds, preset)\n",
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"gen = tts.tts_with_preset(\"They used to say that if man was meant to fly, he’d have wings. But he did fly. He discovered he had to.\", \n",
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" voice_samples=None, conditioning_latents=None, preset=preset)\n",
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"torchaudio.save('captain_kirkard.wav', gen.squeeze(0).cpu(), 24000)\n",
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"torchaudio.save('captain_kirkard.wav', gen.squeeze(0).cpu(), 24000)\n",
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"IPython.display.Audio('captain_kirkard.wav')"
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"IPython.display.Audio('captain_kirkard.wav')"
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],
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],
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@ -150,6 +162,24 @@
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},
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},
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"execution_count": null,
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"execution_count": null,
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"outputs": []
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"del tts # Will break other cells, but necessary to conserve RAM if you want to run this cell.\n",
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"\n",
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"# Tortoise comes with some scripts that does a lot of the lifting for you. For example,\n",
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"# read.py will read a text file for you.\n",
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"!python3 tortoise/read.py --voice=train_atkins --textfile=tortoise/data/riding_hood.txt --preset=ultra_fast --output_path=.\n",
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"\n",
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"IPython.display.Audio('train_atkins/combined.wav')\n",
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"# This will take awhile.."
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],
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"metadata": {
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"id": "t66yqWgu68KL"
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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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]
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}
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}
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