INTROTXT = """# StyleTTS 2 kudos to mrfakename for the base gradio code I'm borrowing here. 日本語用 The Text-guided inference may or may not work. you can only do inference max 512 tokens. ** """ import gradio as gr import styletts2importable import ljspeechimportable import torch import os from txtsplit import txtsplit import numpy as np import pickle theme = gr.themes.Base( font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'], ) voicelist = ['VO_JA_Kamisato_Ayaka_About_Kujou_Sara','hontonokimochi','gaen_original'] voices = {} # import phonemizer # global_phonemizer = phonemizer.backend.EspeakBackend(language='en-us', preserve_punctuation=True, with_stress=True) # todo: cache computed style, load using pickle # if os.path.exists('voices.pkl'): # with open('voices.pkl', 'rb') as f: # voices = pickle.load(f) # else: for v in voicelist: voices[v] = styletts2importable.compute_style(f'voices/{v}.wav') # def synthesize(text, voice, multispeakersteps): # if text.strip() == "": # raise gr.Error("You must enter some text") # # if len(global_phonemizer.phonemize([text])) > 300: # if len(text) > 300: # raise gr.Error("Text must be under 300 characters") # v = voice.lower() # # return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=7, embedding_scale=1)) # return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=multispeakersteps, embedding_scale=1)) if not torch.cuda.is_available(): INTROTXT += "\n\n### You are on a CPU-only system, inference will be much slower.\n\nYou can use the [online demo](https://huggingface.co/spaces/styletts2/styletts2) for fast inference." def synthesize(text, voice, lngsteps, password, progress=gr.Progress()): if text.strip() == "": raise gr.Error("You must enter some text") if len(text) > 50000: raise gr.Error("Text must be <50k characters") print("*** saying ***") print(text) print("*** end ***") texts = txtsplit(text) v = voice.lower() audios = [] for t in progress.tqdm(texts): print(t) audios.append(styletts2importable.inference(t, voices[v], alpha=0.3, beta=0.7, diffusion_steps=lngsteps, embedding_scale=1)) return (24000, np.concatenate(audios)) # def longsynthesize(text, voice, lngsteps, password, progress=gr.Progress()): # if password == os.environ['ACCESS_CODE']: # if text.strip() == "": # raise gr.Error("You must enter some text") # if lngsteps > 25: # raise gr.Error("Max 25 steps") # if lngsteps < 5: # raise gr.Error("Min 5 steps") # texts = split_and_recombine_text(text) # v = voice.lower() # audios = [] # for t in progress.tqdm(texts): # audios.append(styletts2importable.inference(t, voices[v], alpha=0.3, beta=0.7, diffusion_steps=lngsteps, embedding_scale=1)) # return (24000, np.concatenate(audios)) # else: # raise gr.Error('Wrong access code') def clsynthesize(text, voice, vcsteps, embscale, alpha, beta, progress=gr.Progress()): # if text.strip() == "": # raise gr.Error("You must enter some text") # # if global_phonemizer.phonemize([text]) > 300: # if len(text) > 400: # raise gr.Error("Text must be under 400 characters") # # return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=20, embedding_scale=1)) # return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=vcsteps, embedding_scale=1)) if text.strip() == "": raise gr.Error("You must enter some text") if len(text) > 50000: raise gr.Error("Text must be <50k characters") if embscale > 1.3 and len(text) < 20: gr.Warning("WARNING: You entered short text, you may get static!") print("*** saying ***") print(text) print("*** end ***") texts = txtsplit(text) audios = [] # vs = styletts2importable.compute_style(voice) vs = styletts2importable.compute_style(voice) # print(vs) for t in progress.tqdm(texts): audios.append(styletts2importable.inference(t, vs, alpha=alpha, beta=beta, diffusion_steps=vcsteps, embedding_scale=embscale)) # audios.append(styletts2importable.inference(t, vs, diffusion_steps=10, alpha=0.3, beta=0.7, embedding_scale=5)) return (24000, np.concatenate(audios)) def ljsynthesize(text, steps,embscale, progress=gr.Progress()): # if text.strip() == "": # raise gr.Error("You must enter some text") # # if global_phonemizer.phonemize([text]) > 300: # if len(text) > 400: # raise gr.Error("Text must be under 400 characters") noise = torch.randn(1,1,256).to('cuda' if torch.cuda.is_available() else 'cpu') # return (24000, Text-guided Inferenceimportable.inference(text, noise, diffusion_steps=7, embedding_scale=1)) if text.strip() == "": raise gr.Error("You must enter some text") if len(text) > 150000: raise gr.Error("Text must be <150k characters") print("*** saying ***") print(text) print("*** end ***") texts = txtsplit(text) audios = [] for t in progress.tqdm(texts): audios.append(ljspeechimportable.inference(t, noise, diffusion_steps=steps, embedding_scale=embscale)) return (24000, np.concatenate(audios)) with gr.Blocks() as vctk: with gr.Row(): with gr.Column(scale=1): inp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) voice = gr.Dropdown(voicelist, label="Voice", info="Select a default voice.", value='m-us-2', interactive=True) multispeakersteps = gr.Slider(minimum=3, maximum=15, value=3, step=1, label="Diffusion Steps", info="Higher gives you more diverse results but not necessarily higher quality - これを増えたらもっとエモーショナルな結果になりますが、クオリティーのいい結果になるとは限らない。", interactive=True) # use_gruut = gr.Checkbox(label="Use alternate phonemizer (Gruut) - Experimental") with gr.Column(scale=1): btn = gr.Button("Synthesize", variant="primary") audio = gr.Audio(interactive=False, label="Synthesized Audio", waveform_options={'waveform_progress_color': '#3C82F6'}) btn.click(synthesize, inputs=[inp, voice, multispeakersteps], outputs=[audio], concurrency_limit=4) with gr.Blocks() as clone: with gr.Row(): with gr.Column(scale=1): clinp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) clvoice = gr.Audio(label="Voice", interactive=True, type='filepath', max_length=300, waveform_options={'waveform_progress_color': '#3C82F6'}) vcsteps = gr.Slider(minimum=3, maximum=20, value=20, step=1, label="Diffusion Steps", info="Theoretically, higher should be better quality but slower, but we cannot notice a difference. Try with lower steps first - it is faster", interactive=True) embscale = gr.Slider(minimum=1, maximum=10, value=1, step=0.1, label="Embedding Scale (READ WARNING BELOW)", info="Defaults to 1. WARNING: If you set this too high and generate text that's too short you will get static!", interactive=True) alpha = gr.Slider(minimum=0, maximum=1, value=0.3, step=0.1, label="Alpha", info="Defaults to 0.3", interactive=True) beta = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Beta", info="Defaults to 0.7", interactive=True) with gr.Column(scale=1): clbtn = gr.Button("Synthesize", variant="primary") claudio = gr.Audio(interactive=False, label="Synthesized Audio", waveform_options={'waveform_progress_color': '#3C82F6'}) clbtn.click(clsynthesize, inputs=[clinp, clvoice, vcsteps, embscale, alpha, beta], outputs=[claudio], concurrency_limit=4) # with gr.Blocks() as longText: # with gr.Row(): # with gr.Column(scale=1): # lnginp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) # lngvoice = gr.Dropdown(voicelist, label="Voice", info="Select a default voice.", value='m-us-1', interactive=True) # lngsteps = gr.Slider(minimum=5, maximum=25, value=10, step=1, label="Diffusion Steps", info="Higher = better quality, but slower", interactive=True) # lngpwd = gr.Textbox(label="Access code", info="This feature is in beta. You need an access code to use it as it uses more resources and we would like to prevent abuse") # with gr.Column(scale=1): # lngbtn = gr.Button("Synthesize", variant="primary") # lngaudio = gr.Audio(interactive=False, label="Synthesized Audio") # lngbtn.click(longsynthesize, inputs=[lnginp, lngvoice, lngsteps, lngpwd], outputs=[lngaudio], concurrency_limit=4) with gr.Blocks() as lj: with gr.Row(): with gr.Column(scale=1): ljinp = gr.Textbox(label="Text", info="What would you like StyleTTS 2 to read? It works better on full sentences.", interactive=True) embscale = gr.Slider(minimum=1, maximum=10, value=1, step=0.1, label="Embedding Scale (READ WARNING BELOW)", info="Defaults to 1. これを上げたらパフォーマンスがもっとエモーショナルになる、増やしすぎるとだめになるので、ご注意ください", interactive=True) ljsteps = gr.Slider(minimum=3, maximum=20, value=3, step=1, label="Diffusion Steps", info="Theoretically, higher should be better quality but slower, but we cannot notice a difference. Try with lower steps first - it is faster", interactive=True) with gr.Column(scale=1): ljbtn = gr.Button("Synthesize", variant="primary") ljaudio = gr.Audio(interactive=False, label="Synthesized Audio", waveform_options={'waveform_progress_color': '#3C82F6'}) ljbtn.click(ljsynthesize, inputs=[ljinp, ljsteps, embscale], outputs=[ljaudio], concurrency_limit=4) with gr.Blocks(title="StyleTTS 2", css="footer{display:none !important}", theme="NoCrypt/miku") as demo: gr.Markdown(INTROTXT) gr.DuplicateButton("Duplicate Space") # gr.TabbedInterface([vctk, clone, lj, longText], ['Multi-Voice', 'Voice Cloning', 'Text-guided Inference', 'Long Text [Beta]']) gr.TabbedInterface([vctk, clone, lj], ['Multi-Voice', 'do not use this option','Text-guided Inference', 'Long Text [Beta]']) gr.Markdown(""" Demo by [mrfakename](https://twitter.com/realmrfakename). I am not affiliated with the StyleTTS 2 authors. Run this demo locally using Docker: ```bash docker run -it -p 7860:7860 --platform=linux/amd64 --gpus all registry.hf.space/styletts2-styletts2:latest python app.py ``` """) # Please do not remove this line. if __name__ == "__main__": # demo.queue(api_open=False, max_size=15).launch(show_api=False) demo.queue(api_open=False, max_size=15).launch(show_api=False)