New Narrator Version
The narrator and filtering has been re-written to vastly improve filtering of text, resulting in less unwanted sounds and better control over narrator/character.
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erew123 authored and GitHub committed
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@@ -48,7 +48,6 @@ except ModuleNotFoundError:
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# IMPORT - Attempt Importing DeepSpeed (required for displaying Deepspeed checkbox in gradio)
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try:
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import deepspeed
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deepspeed_installed = True
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except ImportError:
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deepspeed_installed = False
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@@ -155,8 +154,8 @@ elif params["tts_method_api_local"] == True:
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elif params["tts_method_xtts_local"] == True:
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gr_modelchoice = "XTTSv2 Local"
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gr_narrator_enabled = str(params["narrator_enabled"]).lower()
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# Set the default for Narrated text without asterisk or quotes to be Narrator
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non_quoted_text_is = True
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######################
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#### GRADIO STUFF ####
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@@ -289,6 +288,21 @@ def send_reload_request(tts_method):
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if json_response.get("status") == "model-success":
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# Update model_loaded to True if the reload was successful
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params["model_loaded"] = True
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# Update local script parameters based on the tts_method
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if tts_method == "API TTS":
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params["tts_method_api_local"] = False
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params["tts_method_xtts_local"] = False
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params["tts_method_api_tts"] = True
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params["deepspeed_activate"] = False
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elif tts_method == "API Local":
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params["tts_method_api_tts"] = False
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params["tts_method_xtts_local"] = False
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params["tts_method_api_local"] = True
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params["deepspeed_activate"] = False
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elif tts_method == "XTTSv2 Local":
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params["tts_method_api_tts"] = False
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params["tts_method_api_local"] = False
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params["tts_method_xtts_local"] = True
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return json_response
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except requests.exceptions.RequestException as e:
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# Handle the HTTP request error
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@@ -402,11 +416,11 @@ def combine(audio_files, output_folder, state):
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audio = np.concatenate((audio, audio_data))
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# Save the combined audio to a file with a specified sample rate
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output_file_path = os.path.join(
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output_folder, f'{state["character_menu"]}_{int(time.time())}_combined.wav'
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)
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if "character_menu" in state:
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output_file_path = os.path.join(output_folder, f'{state["character_menu"]}_{int(time.time())}_combined.wav')
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else:
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output_file_path = os.path.join(output_folder, f'TTSOUT_{int(time.time())}_combined.wav')
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sf.write(output_file_path, audio, samplerate=sample_rate)
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print(f"[{params['branding']}TTSGen] Narrated audio generated")
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# Clean up unnecessary files
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for audio_file in audio_files:
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os.remove(audio_file)
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@@ -463,7 +477,6 @@ def voice_preview(string):
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#################################
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# STANDARD VOICE - Generate TTS Function
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def output_modifier(string, state):
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# DEBUG print("THE ORIGINAL STRING IS:", string,"\n")
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if not params["activate"]:
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return string
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original_string = string
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@@ -477,65 +490,88 @@ def output_modifier(string, state):
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if process_lock.acquire(blocking=False):
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try:
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if params["narrator_enabled"]:
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processed_string = original_string
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processed_string = processed_string.replace("***", "*")
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processed_string = processed_string.replace("**", "*")
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processed_string = processed_string.replace(".*", "*")
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processed_string = processed_string.replace(".'", "'")
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processed_string = processed_string.replace(".'", "'")
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# Remove new lines
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processed_string = processed_string.replace("\n", " ")
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#DEBUG print("PROCESSED STRING IS NOW:", processed_string)
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# Split the processed string into lines
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lines = processed_string.split("\n")
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# Do Some basic stripping and remove any double CR's
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processed_string = (
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original_string
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.replace("***", "*")
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.replace("**", "*")
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.replace("\n\n", "\n")
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)
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# Clean up two asterisks (narrators) being made between a newline, making it one sentence.
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processed_string = re.sub(r'\.\*\n\*', '. ', processed_string)
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# Clean up a few other bits.
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processed_string = (
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processed_string
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.replace("'", "'")
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.replace("\n", " ")
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# Add special characters to the quote so that we can use it to identify things later after its been split
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.replace('"', '"<')
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# Capture new conversations which wont have things like "e in them
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.replace('"', '"<')
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)
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# Set up a tracking of the individual wav files.
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audio_files_all_paragraphs = []
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is_narrator = False
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for line in lines:
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# Decode HTML entities
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decoded_text = html.unescape(line)
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# Initialize variables to track narrator and voice parts
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is_narrator = "*" in line or is_narrator
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# Split the line using double quotes
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parts = re.split(r'"', decoded_text)
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audio_files_paragraph = []
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for i, part in enumerate(parts):
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# Skip parts that are too short
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if len(part.strip()) <= 1:
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continue
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# Determine if it's a narrator or voice part within double quotes
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is_narrator_part = is_narrator if i % 2 == 0 else False
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voice_to_use = (
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params["narrator_voice"] if is_narrator_part else params["voice"]
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)
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# DEBUG print(f"THE STRING TO BE USED: {voice_to_use} {part.strip()}")
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# Process the part
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output_file = Path(
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f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}_{i}.wav'
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)
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output_file_str = output_file.as_posix()
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generate_response = send_generate_request(
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part, voice_to_use, language_code, output_file_str
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)
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audio_path = generate_response.get("data", {}).get("audio_path")
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audio_files_paragraph.append(audio_path)
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is_narrator_part = is_narrator if i % 2 == 0 else False
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voice_to_use = (
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params["narrator_voice"] if is_narrator_part else params["voice"]
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# Split the line using " and ".* " (so end of sentences, leaving special characters added to the start of all OTHER sentences, bar possibly the first one if its starting with a *
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parts = re.split(r'"|\.\*', processed_string)
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audio_files_paragraph = []
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for i, part in enumerate(parts):
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# Skip parts that are too short
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if len(part.strip()) <= 1:
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continue
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# Figure out which type of line it is, then replace characters as necessary to avoid TTS trying to pronunce them, htmlunescape after.
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# Character will always be a < with a letter immediately after it
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if '<' in part and '< *' not in part and '<*' not in part and '< *' not in part and '< ' not in part and '< ' not in part:
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cleaned_part = html.unescape(part.replace('<', ''))
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voice_to_use = params["voice"]
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#Narrator will always be am * or < with an * a position or two after it.
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elif '<*' in part or '< *' in part or '< *' in part or '*' in part:
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cleaned_part = html.unescape(part.replace('<*', '').replace('< *', '').replace('< *', '').replace('*', ''))
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voice_to_use = params["narrator_voice"]
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#If the other two dont capture it, aka, the AI gave no * or " on the line, use non_quoted_text_is aka user interface, user can choose Char or Narrator
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elif non_quoted_text_is:
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cleaned_part = html.unescape(part.replace('< ', '').replace('< ', '').replace('< ', ''))
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voice_to_use = params["voice"]
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else:
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cleaned_part = html.unescape(part.replace('< ', '').replace('< ', '').replace('< ', ''))
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voice_to_use = params["narrator_voice"]
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# Check if character name exists and if not, just call it TTSOUT_
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if "character_menu" in state:
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output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}_{i}.wav')
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else:
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output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}_{i}.wav')
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# Generate that TTS and output to a file
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output_file_str = output_file.as_posix()
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generate_response = send_generate_request(
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cleaned_part, voice_to_use, language_code, output_file_str
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)
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# Accumulate audio files within the paragraph
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audio_files_all_paragraphs.extend(audio_files_paragraph)
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audio_path = generate_response.get("data", {}).get("audio_path")
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audio_files_paragraph.append(audio_path)
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# Accumulate audio files within the paragraph
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audio_files_all_paragraphs.extend(audio_files_paragraph)
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# Combine audio files across paragraphs
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final_output_file = combine(
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audio_files_all_paragraphs, params["output_folder_wav"], state
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)
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else:
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output_file = Path(
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f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav'
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processed_string = (
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original_string
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.replace("***", "")
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.replace("**", "")
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.replace("*", "")
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.replace("\n\n", "\n")
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.replace("'", "'")
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)
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cleaned_part = html.unescape(processed_string)
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# Process the part and give it a non-character name if being used vai API or standalone.
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if "character_menu" in state:
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output_file = Path(f'{params["output_folder_wav"]}/{state["character_menu"]}_{int(time.time())}.wav')
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else:
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output_file = Path(f'{params["output_folder_wav"]}/TTSOUT_{int(time.time())}.wav')
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output_file_str = output_file.as_posix()
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output_file = get_output_filename(state)
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generate_response = send_generate_request(
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string, params["voice"], language_code, output_file_str
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cleaned_part, params["voice"], language_code, output_file_str
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)
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audio_path = generate_response.get("data", {}).get("audio_path")
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final_output_file = audio_path
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@@ -620,6 +656,12 @@ def update_narrator_enabled(value):
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elif value == "Disabled":
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params["narrator_enabled"] = False
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def update_non_quoted_text_is(value):
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global non_quoted_text_is
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if value == "Narrator":
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non_quoted_text_is = False
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elif value == "Char":
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non_quoted_text_is = True
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def input_modifier(string, state):
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if not params["activate"]:
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@@ -702,11 +744,16 @@ def ui():
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},
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"refresh-button",
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)
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narrator_enabled_gr = gr.Radio(
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choices={"Enabled": "true", "Disabled": "false"},
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label="Narrator Activation",
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value="Enabled" if gr_narrator_enabled == "true" else "Disabled",
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)
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narrator_enabled_gr = gr.Radio(
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choices={"Enabled": "true", "Disabled": "false"},
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label="Narrator Activation",
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value="Enabled" if params.get("narrator_enabled") else "Disabled",
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)
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non_quoted_text_is_gr = gr.Radio(
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choices={"Char": "true", "Narrator": "false"},
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label='Text NOT inside of * or " is',
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value="Char" if non_quoted_text_is else "Narrator",
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)
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with gr.Row():
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low_vram = gr.Checkbox(
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@@ -807,9 +854,8 @@ def ui():
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# Narrator selection actions
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narrator_enabled_gr.change(update_narrator_enabled, narrator_enabled_gr, None)
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narrator_voice_gr.change(
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lambda x: params.update({"narrator_voice": x}), narrator_voice_gr, None
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)
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non_quoted_text_is_gr.change(update_non_quoted_text_is, non_quoted_text_is_gr, None)
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narrator_voice_gr.change(lambda x: params.update({"narrator_voice": x}), narrator_voice_gr, None)
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# Play preview
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preview_text.submit(voice_preview, preview_text, preview_audio)
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