import gradio as gr import edge_tts import asyncio import tempfile import os async def get_voices(): voices = await edge_tts.list_voices() voices = [voice for voice in voices if voice.get("Locale") == "de-DE"] return {f"{v['ShortName']} - {v['Locale']} ({v['Gender']})": v['ShortName'] for v in voices} async def text_to_speech(text, voice, rate, pitch): if not text.strip(): return None, "Please enter text to convert." if not voice: return None, "Please select a voice." voice_short_name = voice.split(" - ")[0] rate_str = f"+0%" pitch_str = f"+0Hz" 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 async def tts_interface(text, voice, rate, pitch): audio, warning = await text_to_speech(text, voice, rate, pitch) if warning: return audio, gr.Warning(warning) return audio, None async def create_demo(): voices = await get_voices() description = "" demo = gr.Interface( fn=tts_interface, inputs=[ gr.Textbox(label="Text", lines=5), gr.Dropdown(choices=[""] + list(voices.keys()), label="Stimme", value=""), #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) ], outputs=[ gr.Audio(label="Generated Audio", type="filepath"), gr.Markdown(label="Warning", visible=False) ], title="Text in mp3-Sprachdatei umwandeln", description=description, article="", analytics_enabled=False, allow_flagging="never", api_name=None ) return demo async def main(): demo = await create_demo() demo.queue(default_concurrency_limit=5) demo.launch(show_api=False) if __name__ == "__main__": asyncio.run(main())