Add text splitting

modules/merged_ui/main.py

@@ -4,7 +4,6 @@ import gradio as gr
 from merged_ui.utils import generate_and_process_with_rvc, modified_get_vc
 from rvc_ui.initialization import config
 from rvc_ui.main import names, index_paths
-from spark.sparktts.utils.token_parser import LEVELS_MAP_UI
 
 def build_merged_ui():
     """
@@ -18,6 +17,7 @@ def build_merged_ui():
         with gr.Tabs():
             with gr.TabItem("TTS-to-RVC Pipeline"):
                 gr.Markdown("### Generate speech with Spark TTS and convert with RVC")
+                gr.Markdown("*Note: For multi-sentence text, each sentence will be processed separately and then combined.*")
                 
                 # TTS Generation Section
                 with gr.Row():
@@ -36,7 +36,7 @@ def build_merged_ui():
                     tts_text_input = gr.Textbox(
                         label="Text to synthesize", 
                         lines=3, 
-                        placeholder="Enter text for TTS"
+                        placeholder="Enter text for TTS. Multiple sentences will be processed individually."
                     )
                     prompt_text_input = gr.Textbox(
                         label="Text of prompt speech (Optional)",
@@ -130,8 +130,8 @@ def build_merged_ui():
                 generate_with_rvc_button = gr.Button("Generate with RVC", variant="primary")
                 
                 with gr.Row():
-                    vc_output1 = gr.Textbox(label="Output information")
+                    vc_output1 = gr.Textbox(label="Output information", lines=10)
-                    vc_output2 = gr.Audio(label="Final converted audio")
+                    vc_output2 = gr.Audio(label="Final concatenated audio")
                 
                 # Connect generate function to button
                 generate_with_rvc_button.click(

modules/merged_ui/utils.py

@@ -1,5 +1,10 @@
 import os
 import shutil
+import re
+import numpy as np
+from time import sleep
+import soundfile as sf
+from pydub import AudioSegment
 
 # Import modules from your packages
 from rvc_ui.initialization import vc
@@ -11,31 +16,45 @@ model_dir = "spark/pretrained_models/Spark-TTS-0.5B"
 device = 0
 spark_model = initialize_model(model_dir, device=device)
 
-def generate_and_process_with_rvc(
+def split_into_sentences(text):
-    text, prompt_text, prompt_wav_upload, prompt_wav_record,
+    """
+    Split text into sentences using regular expressions.
+    
+    Args:
+        text (str): The input text to split
+        
+    Returns:
+        list: A list of sentences
+    """
+    # Split on period, exclamation mark, or question mark followed by space or end of string
+    sentences = re.split(r'(?<=[.!?])\s+|(?<=[.!?])$', text)
+    # Remove any empty sentences
+    sentences = [s.strip() for s in sentences if s.strip()]
+    return sentences
+
+def process_single_sentence(
+    sentence_index, sentence, prompt_speech, prompt_text_clean,
     spk_item, vc_transform, f0method, 
     file_index1, file_index2, index_rate, filter_radius,
-    resample_sr, rms_mix_rate, protect
+    resample_sr, rms_mix_rate, protect,
+    base_fragment_num
 ):
     """
-    Handle combined TTS and RVC processing and save outputs to TEMP directories
+    Process a single sentence through the TTS and RVC pipeline
+    
+    Args:
+        sentence_index (int): Index of the sentence in the original text
+        sentence (str): The sentence text to process
+        ... (other parameters are the same as generate_and_process_with_rvc)
+        
+    Returns:
+        tuple: (spark_output_path, rvc_output_path, success, info_message)
     """
-    # Ensure TEMP directories exist
+    fragment_num = base_fragment_num + sentence_index
-    os.makedirs("./TEMP/spark", exist_ok=True)
-    os.makedirs("./TEMP/rvc", exist_ok=True)
-    
-    # Get next fragment number
-    fragment_num = 1
-    while (os.path.exists(f"./TEMP/spark/fragment_{fragment_num}.wav") or 
-           os.path.exists(f"./TEMP/rvc/fragment_{fragment_num}.wav")):
-        fragment_num += 1
-    
-    # First generate TTS audio
-    prompt_speech = prompt_wav_upload if prompt_wav_upload else prompt_wav_record
-    prompt_text_clean = None if not prompt_text or len(prompt_text) < 2 else prompt_text
     
+    # Generate TTS audio for this sentence
     tts_path = run_tts(
-        text,
+        sentence,
         spark_model,
         prompt_text=prompt_text_clean,
         prompt_speech=prompt_speech
@@ -43,7 +62,7 @@ def generate_and_process_with_rvc(
     
     # Make sure we have a TTS file to process
     if not tts_path or not os.path.exists(tts_path):
-        return "Failed to generate TTS audio", None
+        return None, None, False, f"Failed to generate TTS audio for sentence: {sentence}"
     
     # Save Spark output to TEMP/spark
     spark_output_path = f"./TEMP/spark/fragment_{fragment_num}.wav"
@@ -70,7 +89,6 @@ def generate_and_process_with_rvc(
         elif isinstance(output_audio, tuple) and len(output_audio) >= 2:
             # Case 2: output_audio might be (sample_rate, audio_data)
             try:
-                import soundfile as sf
                 sf.write(rvc_output_path, output_audio[1], output_audio[0])
                 rvc_saved = True
             except Exception as inner_e:
@@ -82,14 +100,120 @@ def generate_and_process_with_rvc(
     except Exception as e:
         output_info += f"\nError saving RVC output: {str(e)}"
     
-    # Add file paths to output info
+    # Prepare info message
-    output_info += f"\nSpark output saved to: {spark_output_path}"
+    info_message = f"Sentence {sentence_index+1}: {sentence[:30]}{'...' if len(sentence) > 30 else ''}\n"
+    info_message += f"  - Spark output: {spark_output_path}\n"
     if rvc_saved:
-        output_info += f"\nRVC output saved to: {rvc_output_path}"
+        info_message += f"  - RVC output: {rvc_output_path}"
     else:
-        output_info += f"\nCould not automatically save RVC output to {rvc_output_path}"
+        info_message += f"  - Could not save RVC output to {rvc_output_path}"
     
-    return output_info, output_audio
+    return spark_output_path, rvc_output_path, rvc_saved, info_message
+
+def concatenate_audio_files(file_paths, output_path, sample_rate=44100):
+    """
+    Concatenate multiple audio files into a single file
+    
+    Args:
+        file_paths (list): List of paths to audio files
+        output_path (str): Path to save the concatenated audio
+        sample_rate (int): Sample rate for the output file
+        
+    Returns:
+        bool: True if concatenation was successful, False otherwise
+    """
+    try:
+        # Use pydub to concatenate audio files
+        combined = AudioSegment.empty()
+        for file_path in file_paths:
+            segment = AudioSegment.from_file(file_path)
+            combined += segment
+        
+        # Export the combined audio
+        combined.export(output_path, format="wav")
+        return True
+    except Exception as e:
+        print(f"Error concatenating audio files: {str(e)}")
+        
+        # Fallback method using soundfile
+        try:
+            all_audio = []
+            for file_path in file_paths:
+                data, sr = sf.read(file_path)
+                # Convert to mono if stereo
+                if len(data.shape) > 1 and data.shape[1] > 1:
+                    data = data.mean(axis=1)
+                all_audio.append(data)
+            
+            # Concatenate all audio data
+            concatenated = np.concatenate(all_audio)
+            sf.write(output_path, concatenated, sample_rate)
+            return True
+        except Exception as e2:
+            print(f"Fallback concatenation failed: {str(e2)}")
+            return False
+
+def generate_and_process_with_rvc(
+    text, prompt_text, prompt_wav_upload, prompt_wav_record,
+    spk_item, vc_transform, f0method, 
+    file_index1, file_index2, index_rate, filter_radius,
+    resample_sr, rms_mix_rate, protect
+):
+    """
+    Handle combined TTS and RVC processing for multiple sentences and save outputs to TEMP directories
+    """
+    # Ensure TEMP directories exist
+    os.makedirs("./TEMP/spark", exist_ok=True)
+    os.makedirs("./TEMP/rvc", exist_ok=True)
+    
+    # Split text into sentences
+    sentences = split_into_sentences(text)
+    if not sentences:
+        return "No valid text to process.", None
+    
+    # Get next base fragment number
+    base_fragment_num = 1
+    while any(os.path.exists(f"./TEMP/spark/fragment_{base_fragment_num + i}.wav") or 
+              os.path.exists(f"./TEMP/rvc/fragment_{base_fragment_num + i}.wav") 
+              for i in range(len(sentences))):
+        base_fragment_num += 1
+    
+    # Process reference speech
+    prompt_speech = prompt_wav_upload if prompt_wav_upload else prompt_wav_record
+    prompt_text_clean = None if not prompt_text or len(prompt_text) < 2 else prompt_text
+    
+    # Process each sentence
+    results = []
+    info_messages = [f"Processing {len(sentences)} sentences..."]
+    
+    for i, sentence in enumerate(sentences):
+        spark_path, rvc_path, success, info = process_single_sentence(
+            i, sentence, prompt_speech, prompt_text_clean,
+            spk_item, vc_transform, f0method, 
+            file_index1, file_index2, index_rate, filter_radius,
+            resample_sr, rms_mix_rate, protect,
+            base_fragment_num
+        )
+        
+        info_messages.append(info)
+        if success and rvc_path:
+            results.append(rvc_path)
+    
+    # If no sentences were successfully processed
+    if not results:
+        return "\n".join(info_messages) + "\n\nNo sentences were successfully processed.", None
+    
+    # Concatenate all successful RVC fragments
+    final_output_path = f"./TEMP/final_output_{base_fragment_num}.wav"
+    concatenation_success = concatenate_audio_files(results, final_output_path)
+    
+    if concatenation_success:
+        info_messages.append(f"\nAll fragments concatenated successfully to: {final_output_path}")
+        return "\n".join(info_messages), final_output_path
+    else:
+        # If concatenation failed but we have at least one successful fragment, return the first one
+        info_messages.append(f"\nFailed to concatenate fragments. Returning first successful fragment.")
+        return "\n".join(info_messages), results[0]
 
 def modified_get_vc(sid0_value, protect0_value, file_index2_component):
     """
@@ -101,4 +225,4 @@ def modified_get_vc(sid0_value, protect0_value, file_index2_component):
     if isinstance(outputs, tuple) and len(outputs) >= 3:
         return outputs[0], outputs[1], outputs[3]
     
-    return 0, protect0_value, file_index2_component.choices[0] if file_index2_component.choices else ""
+    return 0, protect0_value, file_index2_component.choices[0] if file_index2_component.choices else ""