Open sekkit opened 1 month ago
hierspeechpp_v1.1_ckpt.pth would be great.
Additionally, you can control the noise_scale_vc during voice conversion. (0.333 would be more robust and 667 would be more diverse.
thx. And I wanna ask what's denoise ratio for, when I set it larger than 0, it always throw CUDA out of memory exception. Even I'm using 4090 24G GPU.
This might solves that issue
# If you have a memory issue during denosing the prompt, try to denoise the prompt with cpu before TTS
# We will have a plan to replace a memory-efficient denoiser
if denoise == 0:
audio = torch.cat([audio.cuda(), audio.cuda()], dim=0)
else:
with torch.no_grad():
if ori_prompt_len > 80000:
denoised_audio = []
for i in range((ori_prompt_len//80000)):
denoised_audio.append(denoise(audio.squeeze(0).cuda()[i*80000:(i+1)*80000], denoiser, hps_denoiser))
denoised_audio.append(denoise(audio.squeeze(0).cuda()[(i+1)*80000:], denoiser, hps_denoiser))
denoised_audio = torch.cat(denoised_audio, dim=1)
else:
denoised_audio = denoise(audio.squeeze(0).cuda(), denoiser, hps_denoiser)
audio = torch.cat([audio.cuda(), denoised_audio[:,:audio.shape[-1]]], dim=0)
audio = audio[:,:ori_prompt_len] # 20231108 We found that large size of padding decreases a performance so we remove the paddings after denosing.
ok, thx, it worked
As the tutorial wrote:
--ckpt "logs/hierspeechpp_libritts460/hierspeechpp_lt460_ckpt.pth" \ LibriTTS-460
--ckpt "logs/hierspeechpp_libritts960/hierspeechpp_lt960_ckpt.pth" \ LibriTTS-960
--ckpt "logs/hierspeechpp_eng_kor/hierspeechpp_v1_ckpt.pth" \ Large_v1 epoch 60 (paper version)
--ckpt "logs/hierspeechpp_eng_kor/hierspeechpp_v1.1_ckpt.pth" \ Large_v1.1 epoch 200 (20. Nov. 2023)
CUDA_VISIBLE_DEVICES=0 python3 inference_vc.py \ --ckpt "logs/hierspeechpp_eng_kor/hierspeechpp_v1.1_ckpt.pth" \ --output_dir "vc_results_eng_kor_v2" \ --noise_scale_vc "0.333" \ --noise_scale_ttv "0.333" \ --denoise_ratio "0"
Which VC model shall I use is the best for crosslingual VC?