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"
description = """
Bark is a universal text-to-audio model created by Suno, with code publicly available here. \
Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects. \
This demo should be used for research purposes only. \
The model output is not censored and the authors do not endorse the opinions in the generated content. \
Use at your own risk.
"""
article = """
## 🌎 Foreign Language
Bark supports various languages out-of-the-box and automatically determines language from input text. \
When prompted with code-switched text, Bark will even attempt to employ the native accent for the respective languages in the same voice.
Try the prompt:
```
Buenos días Miguel. Tu colega piensa que tu alemán es extremadamente malo. But I suppose your english isn't terrible.
```
## 🤭 Non-Speech Sounds
Below is a list of some known non-speech sounds, but we are finding more every day. \
Please let us know if you find patterns that work particularly well on Discord!
* [laughter]
* [laughs]
* [sighs]
* [music]
* [gasps]
* [clears throat]
* — or ... for hesitations
* ♪ for song lyrics
* capitalization for emphasis of a word
* MAN/WOMAN: for bias towards speaker
Try the prompt:
```
" [clears throat] Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as... ♪ singing ♪."
```
## 🎶 Music
Bark can generate all types of audio, and, in principle, doesn't see a difference between speech and music. \
Sometimes Bark chooses to generate text as music, but you can help it out by adding music notes around your lyrics.
Try the prompt:
```
♪ In the jungle, the mighty jungle, the lion barks tonight ♪
```
## 🧬 Voice Cloning
Bark has the capability to fully clone voices - including tone, pitch, emotion and prosody. \
The model also attempts to preserve music, ambient noise, etc. from input audio. \
However, to mitigate misuse of this technology, we limit the audio history prompts to a limited set of Suno-provided, fully synthetic options to choose from.
## 👥 Speaker Prompts
You can provide certain speaker prompts such as NARRATOR, MAN, WOMAN, etc. \
Please note that these are not always respected, especially if a conflicting audio history prompt is given.
Try the prompt:
```
WOMAN: I would like an oatmilk latte please.
MAN: Wow, that's expensive!
```
## Details
Bark model by Suno, including official code and model weights. \
Gradio demo supported by 🤗 Hugging Face. Bark is licensed under the MIT license, see details on GitHub.
"""
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 = """
#share-btn-container {
display: flex;
padding-left: 0.5rem !important;
padding-right: 0.5rem !important;
background-color: #000000;
justify-content: center;
align-items: center;
border-radius: 9999px !important;
width: 13rem;
margin-top: 10px;
margin-left: auto;
flex: unset !important;
}
#share-btn {
all: initial;
color: #ffffff;
font-weight: 600;
cursor: pointer;
font-family: 'IBM Plex Sans', sans-serif;
margin-left: 0.5rem !important;
padding-top: 0.25rem !important;
padding-bottom: 0.25rem !important;
right:0;
}
#share-btn * {
all: unset !important;
}
#share-btn-container div:nth-child(-n+2){
width: auto !important;
min-height: 0px !important;
}
#share-btn-container .wrap {
display: none !important;
}
"""
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()
