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import spaces
import tempfile
import gradio as gr
import os
from whisperspeech.pipeline import Pipeline
import torch
import soundfile as sf
import numpy as np
import torch.nn.functional as F
from whisperspeech.languages import LANGUAGES
from whisperspeech.pipeline import Pipeline
title = """# 🙋🏻♂️ Welcome to🌟Tonic's🌬️💬📝WhisperSpeech
You can use this ZeroGPU Space to test out the current model [🌬️💬📝collabora/whisperspeech](https://huggingface.co/collabora/whisperspeech). 🌬️💬📝collabora/whisperspeech is An Open Source text-to-speech system built by inverting Whisper. Previously known as spear-tts-pytorch. It's like Stable Diffusion but for speech – both powerful and easily customizable.
You can also use 🌬️💬📝WhisperSpeech by cloning this space. 🧬🔬🔍 Simply click here: <a style="display:inline-block" href="https://huggingface.co/spaces/Tonic/laion-whisper?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3>
Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface: [TeamTonic](https://huggingface.co/TeamTonic) & [MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Polytonic](https://github.com/tonic-ai) & contribute to 🌟 [Poly](https://github.com/tonic-ai/poly) 🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
"""
@spaces.GPU
def whisper_speech_demo(text, lang, speaker_audio, mix_lang, mix_text):
pipe = Pipeline()
speaker_url = None
if speaker_audio is not None:
speaker_url = speaker_audio
if mix_lang and mix_text:
mixed_langs = lang.split(',') + mix_lang.split(',')
mixed_texts = [text] + mix_text.split(',')
stoks = pipe.t2s.generate(mixed_texts, lang=mixed_langs)
audio_data = pipe.generate(stoks, speaker_url, lang=mixed_langs[0])
else:
audio_data = pipe.generate(text, speaker_url, lang)
resample_audio = resampler(newsr=24000)
audio_data_resampled = next(resample_audio([{'sample_rate': 22050, 'samples': audio_data.cpu()}]))['samples_24k']
# Normalize
with tempfile.NamedTemporaryFile(delete=False, suffix='.wav') as tmp_file:
tmp_file_name = tmp_file.name
audio_np = audio_data_resampled.numpy() # Convert to numpy array
if audio_np.max() > 1.0 or audio_np.min() < -1.0:
audio_np = audio_np / np.max(np.abs(audio_np))
sf.write(tmp_file_name, audio_np, 24000, 'PCM_24') # Write with a sample rate of 24000 Hz
return tmp_file_name
with gr.Blocks() as demo:
gr.Markdown(title)
with gr.Tabs():
with gr.TabItem("🌬️💬📝Standard TTS"):
with gr.Row():
text_input_standard = gr.Textbox(label="Enter text")
lang_input_standard = gr.Dropdown(choices=list(LANGUAGES.keys()), label="Language")
speaker_input_standard = gr.Audio(label="Upload or Record Speaker Audio (optional)", sources=["upload", "microphone"], type="filepath")
generate_button_standard = gr.Button("Generate Speech")
output_audio_standard = gr.Audio(label="🌬️💬📝WhisperSpeech")
generate_button_standard.click(
whisper_speech_demo,
inputs=[text_input_standard, lang_input_standard, speaker_input_standard, "", ""],
outputs=output_audio_standard
)
with gr.TabItem("🌬️💬📝Mixed Language TTS"):
with gr.Row():
mix_text_input_mixed = gr.Textbox(label="Enter mixed language text", placeholder="e.g., Hello, Cześć")
mix_lang_input_mixed = gr.CheckboxGroup(choices=list(LANGUAGES.keys()), label="Select Languages")
generate_button_mixed = gr.Button("Generate Mixed Speech")
output_audio_mixed = gr.Audio(label="Mixed🌬️💬📝WhisperSpeech")
generate_button_mixed.click(
whisper_speech_demo,
inputs=["", "", "", mix_lang_input_mixed, mix_text_input_mixed],
outputs=output_audio_mixed
)
demo.launch() |