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import gradio as gr
import edge_tts
import asyncio
import tempfile
import os
import json
import datetime
async def get_voices():
voices = await edge_tts.list_voices()
return {
f"{v['ShortName']} - {v['Locale']} ({v['Gender']})": v["ShortName"]
for v in voices
}
def format_time(milliseconds):
"""Convert milliseconds to SRT time format (HH:MM:SS,mmm)"""
# Ensure milliseconds is an integer
milliseconds = int(milliseconds)
seconds, milliseconds = divmod(milliseconds, 1000)
minutes, seconds = divmod(seconds, 60)
hours, minutes = divmod(minutes, 60)
return f"{hours:02d}:{minutes:02d}:{seconds:02d},{milliseconds:03d}"
async def text_to_speech(text, voice, rate, pitch, generate_subtitles=False):
if not text.strip():
return None, None, "Please enter text to convert."
if not voice:
return None, None, "Please select a voice."
voice_short_name = voice.split(" - ")[0]
rate_str = f"{rate:+d}%"
pitch_str = f"{pitch:+d}Hz"
communicate = edge_tts.Communicate(
text, voice_short_name, rate=rate_str, pitch=pitch_str
)
# Create temporary file for audio
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
audio_path = tmp_file.name
subtitle_path = None
if generate_subtitles:
with tempfile.NamedTemporaryFile(delete=False, suffix=".srt") as srt_file:
subtitle_path = srt_file.name
# Generate audio and collect word boundary data
async def process_audio():
word_boundaries = []
async for chunk in communicate.stream():
if chunk["type"] == "audio":
with open(audio_path, "ab") as audio_file:
audio_file.write(chunk["data"])
elif chunk["type"] == "WordBoundary":
word_boundaries.append(chunk)
return word_boundaries
word_boundaries = await process_audio()
# Group words into sensible phrases/sentences for subtitles
phrases = []
current_phrase = []
current_text = ""
phrase_start = 0
for i, boundary in enumerate(word_boundaries):
word = boundary["text"]
start_time = boundary["offset"] / 10000
duration = boundary["duration"] / 10000
end_time = start_time + duration
if not current_phrase:
phrase_start = start_time
current_phrase.append(boundary)
if word in ['.', ',', '!', '?', ':', ';'] or word.startswith(('.', ',', '!', '?', ':', ';')):
current_text = current_text.rstrip() + word + " "
else:
current_text += word + " "
# Determine if we should end this phrase and start a new one
should_break = False
# Break on punctuation
if word.endswith(('.', '!', '?', ':', ';', ',')) or i == len(word_boundaries) - 1:
should_break = True
# Break after a certain number of words (4-5 is typical for subtitles)
elif len(current_phrase) >= 5:
should_break = True
# Break on long pause (more than 300ms between words)
elif i < len(word_boundaries) - 1:
next_start = word_boundaries[i + 1]["offset"] / 10000
if next_start - end_time > 300:
should_break = True
if should_break or i == len(word_boundaries) - 1:
if current_phrase:
last_boundary = current_phrase[-1]
phrase_end = (last_boundary["offset"] + last_boundary["duration"]) / 10000
phrases.append({
"text": current_text.strip(),
"start": phrase_start,
"end": phrase_end
})
current_phrase = []
current_text = ""
# Write phrases to SRT file
with open(subtitle_path, "w", encoding="utf-8") as srt_file:
for i, phrase in enumerate(phrases):
# Write SRT entry
srt_file.write(f"{i+1}\n")
srt_file.write(f"{format_time(phrase['start'])} --> {format_time(phrase['end'])}\n")
srt_file.write(f"{phrase['text']}\n\n")
else:
# Just generate audio
await communicate.save(audio_path)
return audio_path, subtitle_path, None
async def tts_interface(text, voice, rate, pitch, generate_subtitles):
audio, subtitle, warning = await text_to_speech(text, voice, rate, pitch, generate_subtitles)
if warning:
return audio, subtitle, gr.Warning(warning)
return audio, subtitle, None
async def create_demo():
voices = await get_voices()
description = """
Convert text to speech using Microsoft Edge TTS. Adjust speech rate and pitch: 0 is default, positive values increase, negative values decrease.
You can also generate subtitle files (.srt) along with the audio.
**Note:** Edge TTS is a cloud-based service and requires an active internet connection."""
demo = gr.Interface(
fn=tts_interface,
inputs=[
gr.Textbox(label="Input Text", lines=5, value="Hello, how are you doing!"),
gr.Dropdown(
choices=[""] + list(voices.keys()),
label="Select Voice",
value=list(voices.keys())[0] if voices else "",
),
gr.Slider(
minimum=-50,
maximum=50,
value=0,
label="Speech Rate Adjustment (%)",
step=1,
),
gr.Slider(
minimum=-20, maximum=20, value=0, label="Pitch Adjustment (Hz)", step=1
),
gr.Checkbox(label="Generate Subtitles (.srt)", value=False),
],
outputs=[
gr.Audio(label="Generated Audio", type="filepath"),
gr.File(label="Generated Subtitles"),
gr.Markdown(label="Warning", visible=False),
],
title="Edge TTS Text-to-Speech",
description=description,
article="Experience the power of Edge TTS for text-to-speech conversion, and explore our advanced Text-to-Video Converter for even more creative possibilities!",
analytics_enabled=False,
flagging_mode="manual",
api_name="predict",
)
return demo
async def main():
demo = await create_demo()
demo.queue(default_concurrency_limit=50)
demo.launch(show_api=True, show_error=True)
if __name__ == "__main__":
asyncio.run(main())
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