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import gradio as gr
from pdfminer.high_level import extract_text
import logging
from typing import cast
from balacoon_tts import TTS
from huggingface_hub import hf_hub_download, list_repo_files
# Global tts module, initialized from a model selected
tts = None
def read_pdf(file):
with open(file.name, "rb") as f:
text = extract_text(f)
return text
def set_model(model_name_str):
"""
Gets value from `model_name`, loads the model,
re-initializes the tts object, and gets a list of
speakers that the model supports and sets them to `speaker`.
"""
model_path = hf_hub_download(repo_id="balacoon/tts", filename=model_name_str)
global tts
tts = TTS(model_path)
speakers = tts.get_speakers()
value = speakers[-1]
speaker.choices = speakers
speaker.value = value
def main():
logging.basicConfig(level=logging.INFO)
repo_files = list_repo_files(repo_id="balacoon/tts")
model_files = [x for x in repo_files if x.endswith("_cpu.addon")]
model_name_dropdown = gr.inputs.Dropdown(label="Model", choices=model_files)
speaker = gr.inputs.Dropdown(label="Speaker", choices=[])
file_input = gr.inputs.File(label="Select a PDF File", type="file")
text = gr.outputs.Textbox()
def synthesize_audio(file, model_name_str, speaker_str):
"""
Gets the selected PDF `file`, model name from `model_name`,
and speaker name from `speaker`. Synthesizes the audio waveform
from the text extracted from the PDF and returns it.
"""
if file is None or file.name == "":
logging.info("No file selected.")
return None
text_str = read_pdf(file)
if len(text_str) > 1024:
text_str = text_str[:1024]
global tts
samples = cast(TTS, tts).synthesize(text_str, speaker_str)
return (cast(TTS, tts).get_sampling_rate(), samples)
audio = gr.outputs.Audio(label="Generated Audio", type="numpy")
iface = gr.Interface(
fn=synthesize_audio,
inputs=[file_input, model_name_dropdown, speaker],
outputs=audio,
title="PDF TO SPEECH CONVERTER",
layout="rows",
debug=True
)
iface.launch()
if __name__ == "__main__":
main()
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