diff --git a/vall_e/inference.py b/vall_e/inference.py index cc57114..dc5a8f0 100755 --- a/vall_e/inference.py +++ b/vall_e/inference.py @@ -11,7 +11,7 @@ from einops import rearrange from pathlib import Path from .emb import g2p, qnt -from .emb.qnt import trim, trim_random, unload_model +from .emb.qnt import trim, trim_random, unload_model, repeat_extend_audio from .utils import to_device, set_seed, wrapper as ml from .config import cfg, Config @@ -103,7 +103,7 @@ class TTS(): return torch.tensor([ id ]) # to-do: trim before quantizing, instead of after - def encode_audio( self, paths, trim_length=0.0 ): + def encode_audio( self, paths, trim_length=9.0 ): # already a tensor, return it if isinstance( paths, Tensor ): return paths @@ -126,8 +126,14 @@ class TTS(): res = torch.cat(proms) + # kludge, but it's to correct an oversight in training + if trim_length: + res = repeat_extend_audio( res, cfg.dataset.frames_per_second * trim_length ) + + """ if trim_length: res = trim( res, int( cfg.dataset.frames_per_second * trim_length ) ) + """ return res diff --git a/vall_e/webui.py b/vall_e/webui.py index 589af0a..97f166e 100644 --- a/vall_e/webui.py +++ b/vall_e/webui.py @@ -346,7 +346,7 @@ with ui: with gr.Row(): layout["inference_tts"]["inputs"]["max-seconds"] = gr.Slider(value=12, minimum=1, maximum=32, step=0.1, label="Maximum Seconds", info="Limits how many steps to perform in the AR pass.") #layout["inference_tts"]["inputs"]["max-nar-levels"] = gr.Slider(value=7, minimum=0, maximum=7, step=1, label="Max NAR Levels", info="Limits how many steps to perform in the NAR pass.") - layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=3.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Trim Length", info="Trims the input prompt down to X seconds. Set 0 to disable.") + layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=9.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Trim Length", info="Trims the input prompt down to X seconds. Set 0 to disable.") with gr.Row(): layout["inference_tts"]["inputs"]["ar-temp"] = gr.Slider(value=1.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy sample)") layout["inference_tts"]["inputs"]["nar-temp"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (NAR)", info="Modifies the randomness from the samples in the NAR. (0 to greedy sample)")