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( """

Text to Speech with Subtitles

Convert your text to natural-sounding speech and generate subtitles (SRT) for your audio.

""", 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)