Thanks for your help man... TL;DR: - I'm using a radtts model When I try to synthesize Lupe's voice using radtts, I'm passing in radtts' pretrained model that they provide on their repo page here as the feature prediction model...https://github.com/NVIDIA/radtts#radtts-pre-trained-models... alongside the hifigan vocoder trained on Lupe Fiasco's voice by this Colab notebook I got from #841437191073955920 : https://colab.research.google.com/drive/1SKu2xRJy5q1wzuP5CSO8dJ-Nf-UIKz0K This is what the radtts command looks like when it successfully outputs an audible, synthesized .wav using the hifigan vocoder and pretrained radtts model (for feature prediction) that radtts supplies: python3 ./inference.py \ --radtts_path ./radtts_pretrained_dap_model.pt \ --config ./config_ljs_dap.json \ --vocoder_path ./hifigan_vocoder_from_radtts.pt \ --config_vocoder ./hifigan_vocoder_config_from_radtts.json \ --text_path ./tts-input-text.txt \ --speaker ljs \ --speaker_attributes ljs \ --speaker_text ljs \ --output_dir ~/4-tts-outputs/ But that same command outputs that garbled watery noise when I switch out the HG vocoder provided by radtts for the one I got using that Colab notebook I linked to above. Do I have to replace their pretrained model with a new radtts model that I've trained, so that I'm using both a Lupe radtts model for feature prediction and a hifigan Lupe vocoder for audio synthesis as inputs to radtts' inference.py command? Or what am I doing wrong here?