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import gradio as gr | |
import edge_tts | |
import asyncio | |
import tempfile | |
import os | |
from moviepy.editor import AudioFileClip | |
# Get all available voices | |
async def get_voices(): | |
voices = await edge_tts.list_voices() | |
return {f"{v['ShortName']} ({v['Locale']}, {v['Gender']})": v['ShortName'] for v in voices} | |
# Text to speech functionality | |
async def text_to_speech(text, voice, rate, pitch): | |
if not text.strip(): | |
return None, gr.Warning("Please enter the text to convert.") | |
if not voice: | |
return None, gr.Warning("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) | |
with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file: | |
tmp_path = tmp_file.name | |
await communicate.save(tmp_path) | |
return tmp_path, None | |
# Generate SRT file with specified lines of subtitles | |
def generate_srt(words, audio_duration, srt_path, num_lines): | |
with open(srt_path, 'w', encoding='utf-8') as srt_file: | |
segment_duration = audio_duration / (len(words) // (5 * num_lines)) # Average duration for each segment | |
current_time = 0 | |
for i in range(0, len(words), 5 * num_lines): # Adjusting for the number of lines | |
lines = [] | |
for j in range(num_lines): | |
line = ' '.join(words[i + j * 5:i + (j + 1) * 5]) # 5 words per line | |
if line: | |
lines.append(line) | |
start_time = current_time | |
end_time = start_time + segment_duration # Adjust duration for the current segment | |
start_time_str = format_srt_time(start_time) | |
end_time_str = format_srt_time(end_time) | |
srt_file.write(f"{i // (5 * num_lines) + 1}\n{start_time_str} --> {end_time_str}\n" + "\n".join(lines) + "\n\n") | |
current_time += segment_duration # Update current time for the next segment | |
return srt_path | |
def format_srt_time(seconds): | |
millis = int((seconds - int(seconds)) * 1000) | |
seconds = int(seconds) | |
minutes = seconds // 60 | |
hours = minutes // 60 | |
minutes %= 60 | |
seconds %= 60 | |
return f"{hours:02}:{minutes:02}:{seconds:02},{millis:03}" | |
# Text to audio and SRT functionality | |
async def text_to_audio_and_srt(text, voice, rate, pitch, num_lines): | |
audio_path, warning = await text_to_speech(text, voice, rate, pitch) | |
if warning: | |
return None, None, warning | |
audio_clip = AudioFileClip(audio_path) | |
audio_duration = audio_clip.duration | |
# Generate SRT file based on the entire text | |
base_name = os.path.splitext(audio_path)[0] | |
srt_path = f"{base_name}_subtitle.srt" | |
words = text.split() | |
generate_srt(words, audio_duration, srt_path, num_lines) | |
return audio_path, srt_path, None | |
# Gradio interface function | |
def tts_interface(text, voice, rate, pitch, num_lines): | |
audio_path, srt_path, warning = asyncio.run(text_to_audio_and_srt(text, voice, rate, pitch, num_lines)) | |
return audio_path, srt_path, warning | |
# Create Gradio app | |
async def create_demo(): | |
voices = await get_voices() | |
with gr.Blocks() as demo: | |
gr.Markdown( | |
""" | |
<h1 style="text-align: center; color: #333;">Text to Speech with Subtitles</h1> | |
<p style="text-align: center; color: #555;">Convert your text to natural-sounding speech and generate subtitles (SRT) for your audio.</p> | |
""", | |
elem_id="header" | |
) | |
with gr.Row(): | |
with gr.Column(): | |
text_input = gr.Textbox(label="Input Text", lines=5, placeholder="Enter text here...") | |
voice_dropdown = gr.Dropdown(choices=[""] + list(voices.keys()), label="Select Voice", value="") | |
rate_slider = gr.Slider(minimum=-50, maximum=50, value=0, label="Rate Adjustment (%)", step=1) | |
pitch_slider = gr.Slider(minimum=-20, maximum=20, value=0, label="Pitch Adjustment (Hz)", step=1) | |
num_lines_slider = gr.Slider(minimum=1, maximum=5, value=2, label="Number of SRT Lines", step=1) | |
generate_button = gr.Button("Generate Audio and Subtitles", variant="primary") | |
with gr.Column(): | |
output_audio = gr.Audio(label="Generated Audio", type="filepath") | |
output_srt = gr.File(label="Generated SRT", file_count="single") | |
warning_msg = gr.Markdown(label="Warning", visible=False) | |
generate_button.click( | |
fn=tts_interface, | |
inputs=[text_input, voice_dropdown, rate_slider, pitch_slider, num_lines_slider], | |
outputs=[output_audio, output_srt, warning_msg] | |
) | |
return demo | |
# Run the app | |
if __name__ == "__main__": | |
demo = asyncio.run(create_demo()) | |
demo.launch() | |