Spaces:
Running
Running
| # ================================================================================================== | |
| # DEEPFAKE AUDIO - vocoder_preprocess.py (Spectrogram Realignment for Waveform Synthesis) | |
| # ================================================================================================== | |
| # | |
| # 📝 DESCRIPTION | |
| # This script prepares the Ground-Truth Aligned (GTA) mel-spectrograms required 1or | |
| # training the Waveform Vocoder (WaveRNN). By passing training audio through the | |
| # synthesizer and capturing the resulting spectrograms, we ensure that the vocoder | |
| # learns to reconstruct audio from the specific spectral artifacts produced by | |
| # the synthesis engine, rather than just perfect ground truth data. | |
| # | |
| # 👤 AUTHORS | |
| # - Amey Thakur (https://github.com/Amey-Thakur) | |
| # - Mega Satish (https://github.com/msatmod) | |
| # | |
| # 🤝🏻 CREDITS | |
| # Original Real-Time Voice Cloning methodology by CorentinJ | |
| # Repository: https://github.com/CorentinJ/Real-Time-Voice-Cloning | |
| # | |
| # 🔗 PROJECT LINKS | |
| # Repository: https://github.com/Amey-Thakur/DEEPFAKE-AUDIO | |
| # Video Demo: https://youtu.be/i3wnBcbHDbs | |
| # Research: https://github.com/Amey-Thakur/DEEPFAKE-AUDIO/blob/main/DEEPFAKE-AUDIO.ipynb | |
| # | |
| # 📜 LICENSE | |
| # Released under the MIT License | |
| # Release Date: 2021-02-06 | |
| # ================================================================================================== | |
| import argparse | |
| import os | |
| from pathlib import Path | |
| # --- SYNTHETIC PIPELINE MODULES --- | |
| from synthesizer.hparams import hparams | |
| from synthesizer.synthesize import run_synthesis | |
| from utils.argutils import print_args | |
| if __name__ == "__main__": | |
| # --- INTERFACE CONFIGURATION --- | |
| class MyFormatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawDescriptionHelpFormatter): | |
| """Custom formatter to preserve scholarly descriptions.""" | |
| pass | |
| parser = argparse.ArgumentParser( | |
| description="GTA Pre-processor: Generates synthesizer-aligned spectrograms for vocoder training.", | |
| formatter_class=MyFormatter | |
| ) | |
| # --- PATH SPECIFICATIONS --- | |
| parser.add_argument("datasets_root", type=Path, | |
| help="Root directory of the SV2TTS data structure.") | |
| parser.add_argument("-s", "--syn_model_fpath", type=Path, | |
| default="saved_models/default/synthesizer.pt", | |
| help="Path to the trained synthesizer weights used for GTA generation.") | |
| parser.add_argument("-i", "--in_dir", type=Path, default=argparse.SUPPRESS, | |
| help="Input directory (synthesizer-level data). Defaults to <datasets_root>/SV2TTS/synthesizer/.") | |
| parser.add_argument("-o", "--out_dir", type=Path, default=argparse.SUPPRESS, | |
| help="Output directory for GTA features. Defaults to <datasets_root>/SV2TTS/vocoder/.") | |
| # --- COMPUTE PARAMETERS --- | |
| parser.add_argument("--hparams", default="", | |
| help="Acoustic hyperparameter overrides.") | |
| parser.add_argument("--cpu", action="store_true", | |
| help="Enforce CPU-only processing for GTA synthesis.") | |
| args = parser.parse_args() | |
| # --- ARCHITECTURAL ORCHESTRATION --- | |
| print_args(args, parser) | |
| print("🤝🏻 Scholarly Partnership: Amey Thakur & Mega Satish") | |
| print("🚀 Extracting Ground-Truth Aligned mel-spectrograms...") | |
| modified_hp = hparams.parse(args.hparams) | |
| # Resolution of default paths within the SV2TTS ecosystem. | |
| if not hasattr(args, "in_dir"): | |
| args.in_dir = args.datasets_root / "SV2TTS" / "synthesizer" | |
| if not hasattr(args, "out_dir"): | |
| args.out_dir = args.datasets_root / "SV2TTS" / "vocoder" | |
| # Hardware masking for CPU-constrained environments. | |
| if args.cpu: | |
| os.environ["CUDA_VISIBLE_DEVICES"] = "-1" | |
| # Execute the GTA synthesis engine. | |
| run_synthesis(args.in_dir, args.out_dir, args.syn_model_fpath, modified_hp) | |