nnf_text_to_speech_v1 / bark_exemple.py
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import numpy as np
import gradio as gr
from bark import SAMPLE_RATE, generate_audio, preload_models
from bark.generation import SUPPORTED_LANGS
from share_btn import community_icon_html, loading_icon_html, share_js
DEBUG_MODE = False
if not DEBUG_MODE:
_ = preload_models()
AVAILABLE_PROMPTS = ["Unconditional", "Announcer"]
PROMPT_LOOKUP = {}
for _, lang in SUPPORTED_LANGS:
for n in range(10):
label = f"Speaker {n} ({lang})"
AVAILABLE_PROMPTS.append(label)
PROMPT_LOOKUP[label] = f"{lang}_speaker_{n}"
PROMPT_LOOKUP["Unconditional"] = None
PROMPT_LOOKUP["Announcer"] = "announcer"
default_text = "Hello, my name is Suno. And, uh — and I like pizza. [laughs]\nBut I also have other interests such as playing tic tac toe."
title = "# 🐶 Bark</div>"
description = """
"""
article = """
"""
examples = [
["Please surprise me and speak in whatever voice you enjoy. Vielen Dank und Gesundheit!",
"Unconditional"], # , 0.7, 0.7],
["Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as playing tic tac toe.",
"Speaker 1 (en)"], # , 0.7, 0.7],
["Buenos días Miguel. Tu colega piensa que tu alemán es extremadamente malo. But I suppose your english isn't terrible.",
"Speaker 0 (es)"], # , 0.7, 0.7],
]
def gen_tts(text, history_prompt): # , temp_semantic, temp_waveform):
history_prompt = PROMPT_LOOKUP[history_prompt]
if DEBUG_MODE:
audio_arr = np.zeros(SAMPLE_RATE)
else:
# , text_temp=temp_semantic, waveform_temp=temp_waveform)
audio_arr = generate_audio(text, history_prompt=history_prompt)
audio_arr = (audio_arr * 32767).astype(np.int16)
return (SAMPLE_RATE, audio_arr)
css = """
"""
with gr.Blocks(css=css) as block:
gr.Markdown(title)
gr.Markdown(description)
with gr.Row():
with gr.Column():
input_text = gr.Textbox(
label="Input Text", lines=2, value=default_text, elem_id="input_text")
options = gr.Dropdown(
AVAILABLE_PROMPTS, value="Speaker 1 (en)", label="Acoustic Prompt", elem_id="speaker_option")
run_button = gr.Button(text="Generate Audio", type="button")
with gr.Column():
audio_out = gr.Audio(label="Generated Audio",
type="numpy", elem_id="audio_out")
with gr.Row(visible=False) as share_row:
with gr.Group(elem_id="share-btn-container"):
community_icon = gr.HTML(community_icon_html)
loading_icon = gr.HTML(loading_icon_html)
share_button = gr.Button(
"Share to community", elem_id="share-btn")
share_button.click(None, [], [], _js=share_js)
inputs = [input_text, options]
outputs = [audio_out]
gr.Examples(examples=examples, fn=gen_tts, inputs=inputs,
outputs=outputs, cache_examples=True)
gr.Markdown(article)
run_button.click(fn=lambda: gr.update(visible=False), inputs=None, outputs=share_row, queue=False).then(
fn=gen_tts, inputs=inputs, outputs=outputs, queue=True).then(
fn=lambda: gr.update(visible=True), inputs=None, outputs=share_row, queue=False)
block.queue()
block.launch()