import os os.environ["NUMBA_DISABLE_CACHE"] = "1" import os import gradio as gr from docx import Document from TTS.api import TTS import tempfile import zipfile from io import BytesIO import re from pydub import AudioSegment final_audio = AudioSegment.empty() # Voice model VOICE_MODEL = "tts_models/en/vctk/vits" # Embedded metadata (from your file) SPEAKER_METADATA = { 300: { "age": 23, "gender": "F", "accent": "American"}, 271: { "age": 19, "gender": "M", "accent": "Scottish"}, 287: { "age": 23, "gender": "M", "accent": "English"}, 262: { "age": 23, "gender": "F", "accent": "Scottish"}, 284: { "age": 20, "gender": "M", "accent": "Scottish"}, 297: { "age": 20, "gender": "F", "accent": "American"}, 227: { "age": 38, "gender": "M", "accent": "English"}, 246: { "age": 22, "gender": "M", "accent": "Scottish"}, 225: { "age": 23, "gender": "F", "accent": "English"}, 259: { "age": 23, "gender": "M", "accent": "English"}, 252: { "age": 22, "gender": "M", "accent": "Scottish"}, 231: { "age": 23, "gender": "F", "accent": "English"}, 266: { "age": 22, "gender": "F", "accent": "Irish"}, 241: { "age": 21, "gender": "M", "accent": "Scottish"}, 312: { "age": 19, "gender": "F", "accent": "Canadian"}, 329: { "age": 23, "gender": "F", "accent": "American"}, 232: { "age": 23, "gender": "M", "accent": "English"}, 305: { "age": 19, "gender": "F", "accent": "American"}, 311: { "age": 21, "gender": "M", "accent": "American"}, 301: { "age": 23, "gender": "F", "accent": "American"}, 304: { "age": 22, "gender": "M", "accent": "NorthernIrish"}, 310: { "age": 21, "gender": "F", "accent": "American"}, 260: { "age": 21, "gender": "M", "accent": "Scottish"}, 315: { "age": 18, "gender": "M", "accent": "American"}, 374: { "age": 28, "gender": "M", "accent": "Australian"}, 364: { "age": 23, "gender": "M", "accent": "Irish"}, 269: { "age": 20, "gender": "F", "accent": "English"}, 345: { "age": 22, "gender": "M", "accent": "American"}, 326: { "age": 26, "gender": "M", "accent": "Australian"}, 343: { "age": 27, "gender": "F", "accent": "Canadian"}, 230: { "age": 22, "gender": "F", "accent": "English"}, 376: { "age": 22, "gender": "M", "accent": "Indian"}, 240: { "age": 21, "gender": "F", "accent": "English"}, 298: { "age": 19, "gender": "M", "accent": "Irish"}, 272: { "age": 23, "gender": "M", "accent": "Scottish"}, 248: { "age": 23, "gender": "F", "accent": "Indian"}, 264: { "age": 23, "gender": "F", "accent": "Scottish"}, 250: { "age": 22, "gender": "F", "accent": "English"}, 292: { "age": 23, "gender": "M", "accent": "NorthernIrish"}, 237: { "age": 22, "gender": "M", "accent": "Scottish"}, 363: { "age": 22, "gender": "M", "accent": "Canadian"}, 313: { "age": 24, "gender": "F", "accent": "Irish"}, 285: { "age": 21, "gender": "M", "accent": "Scottish"}, 268: { "age": 23, "gender": "F", "accent": "English"}, 302: { "age": 20, "gender": "M", "accent": "Canadian"}, 261: { "age": 26, "gender": "F", "accent": "NorthernIrish"}, 336: { "age": 18, "gender": "F", "accent": "SouthAfrican"}, 288: { "age": 22, "gender": "F", "accent": "Irish"}, 226: { "age": 22, "gender": "M", "accent": "English"}, 277: { "age": 23, "gender": "F", "accent": "English"}, 360: { "age": 19, "gender": "M", "accent": "American"}, 257: { "age": 24, "gender": "F", "accent": "English"}, 254: { "age": 21, "gender": "M", "accent": "English"}, 339: { "age": 21, "gender": "F", "accent": "American"}, 323: { "age": 19, "gender": "F", "accent": "SouthAfrican"}, 255: { "age": 19, "gender": "M", "accent": "Scottish"}, 249: { "age": 22, "gender": "F", "accent": "Scottish"}, 293: { "age": 22, "gender": "F", "accent": "NorthernIrish"}, 244: { "age": 22, "gender": "F", "accent": "English"}, 245: { "age": 25, "gender": "M", "accent": "Irish"}, 361: { "age": 19, "gender": "F", "accent": "American"}, 314: { "age": 26, "gender": "F", "accent": "SouthAfrican"}, 308: { "age": 18, "gender": "F", "accent": "American"}, 229: { "age": 23, "gender": "F", "accent": "English"}, 341: { "age": 26, "gender": "F", "accent": "American"}, 275: { "age": 23, "gender": "M", "accent": "Scottish"}, 263: { "age": 22, "gender": "M", "accent": "Scottish"}, 253: { "age": 22, "gender": "F", "accent": "Welsh"}, 299: { "age": 25, "gender": "F", "accent": "American"}, 316: { "age": 20, "gender": "M", "accent": "Canadian"}, 282: { "age": 23, "gender": "F", "accent": "English"}, 362: { "age": 29, "gender": "F", "accent": "American"}, 294: { "age": 33, "gender": "F", "accent": "American"}, 274: { "age": 22, "gender": "M", "accent": "English"}, 279: { "age": 23, "gender": "M", "accent": "English"}, 281: { "age": 29, "gender": "M", "accent": "Scottish"}, 286: { "age": 23, "gender": "M", "accent": "English"}, 258: { "age": 22, "gender": "M", "accent": "English"}, 247: { "age": 22, "gender": "M", "accent": "Scottish"}, 351: { "age": 21, "gender": "F", "accent": "NorthernIrish"}, 283: { "age": 24, "gender": "F", "accent": "Irish"}, 334: { "age": 18, "gender": "M", "accent": "American"}, 333: { "age": 19, "gender": "F", "accent": "American"}, 295: { "age": 23, "gender": "F", "accent": "Irish"}, 330: { "age": 26, "gender": "F", "accent": "American"}, 335: { "age": 25, "gender": "F", "accent": "NewZealand"}, 228: { "age": 22, "gender": "F", "accent": "English"}, 267: { "age": 23, "gender": "F", "accent": "English"}, 273: { "age": 18, "gender": "F", "accent": "English"} } def clean_text(text): # Remove hyperlinks return re.sub(r'http[s]?://\S+', '', text) def extract_paragraphs_from_docx(docx_file): document = Document(docx_file.name) paragraphs = [p.text.strip() for p in document.paragraphs if p.text.strip()] return [clean_text(p) for p in paragraphs] def list_speaker_choices(): return [f"{sid} | {meta['gender']} | {meta['accent']}" for sid, meta in SPEAKER_METADATA.items()] def get_speaker_id_from_label(label): return label.split('|')[0].strip() def generate_sample_audio(sample_text, speaker_label): if len(sample_text) > 500: raise gr.Error("Sample text exceeds 500 characters.") speaker_id = get_speaker_id_from_label(speaker_label) model = TTS("tts_models/en/vctk/vits") with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav: model.tts_to_file(text=sample_text, speaker="p"+speaker_id, file_path=tmp_wav.name) return tmp_wav.name def generate_audio(docx_file, speaker_label): speaker_id = get_speaker_id_from_label(speaker_label) model = TTS("tts_models/en/vctk/vits") paragraphs = extract_paragraphs_from_docx(docx_file) combined_audio = AudioSegment.empty() temp_files = [] try: for idx, para in enumerate(paragraphs): tmp = tempfile.NamedTemporaryFile(suffix=".wav", delete=False) model.tts_to_file(text=para, speaker="p"+speaker_id, file_path=tmp.name) audio_chunk = AudioSegment.from_wav(tmp.name) combined_audio += audio_chunk temp_files.append(tmp.name) tmp.close() except Exception as e: print("Generation interrupted. Saving partial output.", e) output_dir = tempfile.mkdtemp() final_output_path = os.path.join(output_dir, "final_output.wav") combined_audio.export(final_output_path, format="wav") zip_path = os.path.join(output_dir, "output.zip") with zipfile.ZipFile(zip_path, 'w') as zipf: zipf.write(final_output_path, arcname="final_output.wav") for f in temp_files: os.remove(f) return zip_path # --- UI --- speaker_choices = list_speaker_choices() with gr.Blocks() as demo: gr.Markdown("## 📄 TTS Voice Generator with Paragraph-Wise Processing") with gr.Row(): speaker_dropdown = gr.Dropdown(label="Select Voice", choices=speaker_choices) with gr.Row(): sample_textbox = gr.Textbox(label="Enter Sample Text (Max 500 characters)", max_lines=5) sample_button = gr.Button("Generate Sample") clear_button = gr.Button("Clear Sample") sample_audio = gr.Audio(label="Sample Output", type="filepath") sample_button.click(fn=generate_sample_audio, inputs=[sample_textbox, speaker_dropdown], outputs=[sample_audio]) clear_button.click(fn=lambda: None, inputs=[], outputs=[sample_audio]) with gr.Row(): docx_input = gr.File(label="Upload DOCX File", file_types=[".docx"]) generate_button = gr.Button("Generate Full Audio") download_output = gr.File(label="Download Output Zip") generate_button.click(fn=generate_audio, inputs=[docx_input, speaker_dropdown], outputs=[download_output]) if __name__ == "__main__": demo.launch()