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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, output_path): | |
| if not text.strip(): | |
| return None, gr.Warning("Please enter the text to convert into voice") | |
| 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) | |
| # Save to the specified output path | |
| await communicate.save(output_path) | |
| return output_path, None | |
| # 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: | |
| total_segments = max(len(words) // (5 * num_lines), 1) # Ensure at least one segment | |
| segment_duration = audio_duration / total_segments | |
| current_time = 0 | |
| for i in range(0, len(words), 5 * num_lines): | |
| lines = [] | |
| for j in range(num_lines): | |
| line_start = i + j * 5 | |
| line_end = line_start + 5 | |
| line = ' '.join(words[line_start:line_end]) | |
| if line: | |
| lines.append(line) | |
| start_time = current_time | |
| end_time = start_time + segment_duration | |
| 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 | |
| return srt_path | |
| # def generate_srt(words, audio_duration, srt_path, num_lines): | |
| # with open(srt_path, 'w', encoding='utf-8') as srt_file: | |
| # divisor = len(words) // (5 * num_lines) | |
| # if divisor == 0: | |
| # segment_duration = audio_duration # Use full duration as fallback | |
| # else: | |
| # segment_duration = audio_duration / divisor # Calculate duration per segment | |
| # current_time = 0 | |
| # for i in range(0, len(words), 5 * num_lines): | |
| # lines = [] | |
| # for j in range(num_lines): | |
| # line = ' '.join(words[i + j * 5:i + (j + 1) * 5]) | |
| # if line: | |
| # lines.append(line) | |
| # start_time = current_time | |
| # end_time = start_time + segment_duration | |
| # 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 | |
| # 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, output_audio_path, output_srt_path): | |
| audio_path, warning = await text_to_speech(text, voice, rate, pitch, output_audio_path) | |
| if warning: | |
| return None, None, warning | |
| audio_clip = AudioFileClip(audio_path) | |
| audio_duration = audio_clip.duration | |
| # Generate SRT file based on the entire text | |
| words = text.split() | |
| generate_srt(words, audio_duration, output_srt_path, num_lines) | |
| return audio_path, output_srt_path, None | |
| # 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, output_audio_path="output_audio.mp3", output_srt_path="output_subtitle.srt"): | |
| if not text.strip(): | |
| return None, None, gr.Warning("Text input cannot be empty.") | |
| if num_lines <= 0: | |
| return None, None, gr.Warning("Number of SRT lines must be greater than zero.") | |
| try: | |
| audio_path, srt_path, warning = asyncio.run( | |
| text_to_audio_and_srt(text, voice, rate, pitch, num_lines, output_audio_path, output_srt_path) | |
| ) | |
| return audio_path, srt_path, warning | |
| except Exception as e: | |
| return None, None, gr.Warning(f"An error occurred: {e}") | |
| # 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(show_error=True) | |