Open Shenkailai opened 1 month ago
config: { "train": { "log_interval": 200, "eval_interval": 1000, "seed": 2024, "epochs": 20000, "learning_rate": 2e-4, "betas": [0.8, 0.99], "eps": 1e-9, "batch_size": 32, "fp16_run": false, "lr_decay": 0.999875, "segment_size": 16384 , "init_lr_ratio": 1, "warmup_epochs": 0, "c_mel": 45, "c_kl": 1.0, "fft_sizes": [768, 1366, 342], "hop_sizes": [60, 120, 20], "win_lengths": [300, 600, 120], "window": "hann_window" }, "data": { "use_mel_posterior_encoder": true, "training_files":"filelists/all/train.txt.cleaned3", "validation_files":"filelists/all/val.txt.cleaned3", "max_wav_value": 32768.0, "sampling_rate": 16000, "filter_length": 2048, "hop_length": 512, "win_length": 2048, "n_mel_channels": 80, "mel_fmin": 0.0, "mel_fmax": null, "add_blank": true, "n_speakers": 1304, "cleaned_text": true }, "model": { "use_mel_posterior_encoder": true, "use_transformer_flows": true, "transformer_flow_type": "pre_conv2", "use_spk_conditioned_encoder": true, "use_noise_scaled_mas": true, "use_duration_discriminator": true, "duration_discriminator_type": "dur_disc_2", "ms_istft_vits": false, "mb_istft_vits": true, "istft_vits": false, "subbands": 4, "gen_istft_n_fft": 16, "gen_istft_hop_size": 4, "inter_channels": 192, "hidden_channels": 96, "filter_channels": 768, "n_heads": 2, "n_layers": 3, "kernel_size": 3, "p_dropout": 0.1, "resblock": "1", "resblock_kernel_sizes": [3,7,11], "resblock_dilation_sizes": [[1,3,5], [1,3,5], [1,3,5]], "upsample_rates": [4,4,2], "upsample_initial_channel": 256, "upsample_kernel_sizes": [16,16,8], "n_layers_q": 3, "use_spectral_norm": false, "use_sdp": false, "gin_channels": 256 } }
In addition, I have also adopted the frontend processing method for both Chinese and English from GPT-SoVITS: https://github.com/RVC-Boss/GPT-SoVITS/tree/main/GPT_SoVITS/text.
However, it seems that the original MB-iSTFT-VITS2 (without any modifications) also exhibits this issue on LJSpeech.
dali.zip (279000 steps)
This is a synthesized 16kHz Chinese audio, where noise is consistently present at specific frequencies.