mirror of
https://github.com/coqui-ai/TTS.git
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a3d5801c44
* initial commit * Tortoise inference * revert path change * style fix * remove accidental remove * style fixes * style fixes * removed unwanted assests and deps * remove changes * remove cvvp * style fix black * added tortoise config and updated config and args, refactoring the code * added tortoise to api * Pull mel_norm from url * Use TTS cleaners * Let download model files * add ability to pass tortoise presets through coqui api * fix tests * fix style and tests * fix tts commandline for tortoise * Add config.json to tortoise * Use kwargs * Use regular model api for loading tortoise * Add load from dir to synthesizer * Fix Tortoise floats * Use model_dir when there are multiple urls * Use `synthesize` when exists * lint fixes and resolve preset bug * resolve a download bug and update model link * fix json * do tortoise inference from voice dir * fix * fix test * fix speaker id and remove assests * update inference_tests.yml * replace inference_test.yml * fix extra dir as None * fix tests * remove space * Reformat docstring * Add docs * Update docs * lint fixes --------- Co-authored-by: Eren Gölge <egolge@coqui.ai> Co-authored-by: Eren Gölge <erogol@hotmail.com>
109 lines
3.3 KiB
Plaintext
109 lines
3.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4d50310e-f094-42e0-af30-1e42b13ceb95",
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"metadata": {},
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"outputs": [],
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"source": [
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"#@title # Setup\n",
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"# Imports used through the rest of the notebook.\n",
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"import torch\n",
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"import torchaudio\n",
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"import torch.nn as nn\n",
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"import torch.nn.functional as F\n",
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"\n",
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"import IPython\n",
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"\n",
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"from TTS.tts.models.tortoise import TextToSpeech\n",
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"from TTS.tts.layers.tortoise.audio_utils import load_audio, load_voice, load_voices\n",
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"\n",
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"# This will download all the models used by Tortoise from the HuggingFace hub.\n",
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"tts = TextToSpeech()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e126c3c3-d90a-492f-b5bb-0d86587f15cc",
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"metadata": {},
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"outputs": [],
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"source": [
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"# This is the text that will be spoken.\n",
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"text = \"Joining two modalities results in a surprising increase in generalization! What would happen if we combined them all?\" #@param {type:\"string\"}\n",
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"#@markdown Show code for multiline text input\n",
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"# Here's something for the poetically inclined.. (set text=)\n",
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"\"\"\"\n",
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"Then took the other, as just as fair,\n",
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"And having perhaps the better claim,\n",
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"Because it was grassy and wanted wear;\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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"\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\" #@param [\"ultra_fast\", \"fast\", \"standard\", \"high_quality\"]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9413f553-5bd0-4820-bad4-edd7fd7d2370",
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"metadata": {},
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"outputs": [],
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"source": [
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"%ls ../TTS/tts/utils/assets/tortoise/voices/\n",
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"import IPython\n",
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"IPython.display.Audio(filename='../TTS/tts/utils/assets/tortoise/voices/lj/1.wav')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "96a98ae5-313b-40d1-9311-5a785f2c9a4e",
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"metadata": {},
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"outputs": [],
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"source": [
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"#@markdown Pick one of the voices from the output above\n",
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"voice = 'lj' #@param {type:\"string\"}\n",
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"\n",
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"#@markdown 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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"IPython.display.Audio('generated.wav')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "04e473e5-c489-4a78-aa11-03e89a778ed8",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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