Update app.py

app.py

@@ -118,174 +118,94 @@ SPEAKER_METADATA = {
 
 
 
+# Bark prompts (example)
+BARK_PROMPTS = [
+    "Shy girl",
+    "Old man",
+    "Excited child",
+    "Angry woman"
+]
 
-# Voice model
-VOICE_MODEL = "tts_models/en/vctk/vits"
-
-
-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 list_speaker_choices(metadata):
+    """Helper function to list speakers from metadata (for VCTK and Coqui)"""
+    return [f"Speaker {sid} | {meta['gender']} | {meta['accent']}" for sid, meta in metadata.items()]
 
 def get_speaker_id_from_label(label):
+    """Extract speaker ID from label string"""
     return label.split('|')[0].strip()
 
-# Bark Voice List (Textual Prompts)
-bark_voice_choices = [
-    "young female voice",
-    "middle-aged male voice with British accent",
-    "calm narrator",
-    "excited teenager",
-    "elderly male voice",
-    "child with American accent"
-]
-
-# Function to generate audio using Coqui TTS (with metadata)
-def generate_sample_audio(sample_text, speaker_label, model_choice):
-    if len(sample_text) > 500:
-        raise gr.Error("Sample text exceeds 500 characters.")
-    
+def generate_audio(sample_text, speaker_label, engine):
+    """Generate audio based on engine choice"""
     speaker_id = get_speaker_id_from_label(speaker_label)
+    model = None
+
+    # Engine selection logic
+    if engine == "bark":
+        model = TTS("bark_model_path")  # Replace with actual path for Bark model
+    elif engine == "coqui":
+        model = TTS("coqui_model_path")  # Replace with actual path for Coqui model
+    elif engine == "vctk":
+        model = TTS(VOICE_MODEL)  # Replace with actual path for VCTK model
+
+    # Temporary file creation for output audio
+    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
+
+# --- UI Components ---
+with gr.Blocks() as demo:
+    gr.Markdown("## 📄 TTS Voice Generator with Multiple Engines")
     
-    if model_choice == "Coqui":
-        model = TTS("tts_models/multilingual/multi-dataset/your_model")
-        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
-    elif model_choice == "Bark":
-        voice_prompt = speaker_label  # Bark's speaker prompt could be a descriptive voice label
-        audio = generate_audio(sample_text, speaker_prompt=voice_prompt)  # Bark's method for audio generation
-        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav:
-            audio.export(tmp_wav.name, format="wav")
-            return tmp_wav.name
-    else:
-        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
-
-# Function to generate full audio from DOCX using selected TTS model
-def generate_audio(docx_file, speaker_label, model_choice):
-    speaker_id = get_speaker_id_from_label(speaker_label)
+    # Engine dropdown
+    engine_dropdown = gr.Dropdown(
+        label="Select TTS Engine", 
+        choices=["bark", "coqui", "vctk"], 
+        value="vctk"
+    )
+
+    # Speaker/Prompt dropdown (dynamic)
+    speaker_dropdown = gr.Dropdown(label="Select Speaker", visible=False)
+    prompt_dropdown = gr.Dropdown(label="Select Prompt", visible=False)
+
+    # Sample text box
+    sample_textbox = gr.Textbox(label="Enter Sample Text (Max 500 characters)", max_lines=5, max_chars=500)
+    sample_audio = gr.Audio(label="Sample Output Audio", type="filepath")
     
-    if model_choice == "Coqui":
-        model = TTS("tts_models/multilingual/multi-dataset/your_model")
-        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
+    # Define metadata choices for speakers (Coqui and VCTK)
+    speaker_choices_vctk_coqui = list_speaker_choices(SPEAKER_METADATA)
+    speaker_dropdown.choices = speaker_choices_vctk_coqui  # Use metadata for VCTK/Coqui speakers
 
-    elif model_choice == "Bark":
-        paragraphs = extract_paragraphs_from_docx(docx_file)
-        combined_audio = AudioSegment.empty()
-        
-        try:
-            for para in paragraphs:
-                audio = generate_audio(para, speaker_prompt=speaker_label)  # Bark
-                combined_audio += audio  # Append audio to final output
-        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")
-        
-        return zip_path
-
-    else:  # VCTK
-        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("tts_models/en/vctk/vits")
-                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():
-        model_selector = gr.Dropdown(label="Select TTS Engine", choices=["Coqui", "Bark", "VCTK"], value="VCTK")
-        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, model_selector], 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")
+    # Define Bark prompts (choose from predefined prompts)
+    prompt_dropdown.choices = BARK_PROMPTS
+    
+    # Dynamically update dropdown visibility based on engine selection
+    def update_dropdowns(engine):
+        if engine == "bark":
+            speaker_dropdown.visible = False
+            prompt_dropdown.visible = True
+        elif engine == "coqui" or engine == "vctk":
+            speaker_dropdown.visible = True
+            prompt_dropdown.visible = False
+        return gr.update(visible=speaker_dropdown.visible), gr.update(visible=prompt_dropdown.visible)
+
+    # Trigger dropdown visibility changes
+    engine_dropdown.change(update_dropdowns, inputs=engine_dropdown, outputs=[speaker_dropdown, prompt_dropdown])
+
+    # Button to generate audio from sample text
+    generate_button = gr.Button("Generate Audio")
+    generate_button.click(
+        fn=generate_audio, 
+        inputs=[sample_textbox, speaker_dropdown, engine_dropdown], 
+        outputs=[sample_audio]
+    )
+
+    # Button to clear the sample text and audio
+    def clear_sample():
+        return "", None
+
+    clear_button = gr.Button("Clear")
+    clear_button.click(fn=clear_sample, inputs=[], outputs=[sample_textbox, sample_audio])
 
-    generate_button.click(fn=generate_audio, inputs=[docx_input, speaker_dropdown, model_selector], outputs=[download_output])
 
 if __name__ == "__main__":
     demo.launch()