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import argparse |
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import numpy as np |
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from bark import SAMPLE_RATE, generate_audio, preload_models |
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import os |
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import datetime |
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import soundfile as sf |
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import re |
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SUPPORTED_LANGS = [ |
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("English", "en"), |
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("German", "de"), |
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("Spanish", "es"), |
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("French", "fr"), |
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("Hindi", "hi"), |
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("Italian", "it"), |
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("Japanese", "ja"), |
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("Korean", "ko"), |
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("Polish", "pl"), |
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("Portuguese", "pt"), |
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("Russian", "ru"), |
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("Turkish", "tr"), |
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("Chinese", "zh"), |
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] |
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ALLOWED_PROMPTS = set() |
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ALLOWED_PROMPTS = {"announcer"} |
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for _, lang in SUPPORTED_LANGS: |
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for n in range(10): |
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ALLOWED_PROMPTS.add(f"{lang}_speaker_{n}") |
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for n in range(10): |
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ALLOWED_PROMPTS.add(f"speaker_{n}") |
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def estimate_spoken_time(text, wpm=150, time_limit=14): |
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text_without_brackets = re.sub(r'\[.*?\]', '', text) |
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words = text_without_brackets.split() |
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word_count = len(words) |
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time_in_seconds = (word_count / wpm) * 60 |
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if time_in_seconds > time_limit: |
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return True, time_in_seconds |
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else: |
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return False, time_in_seconds |
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def save_audio_to_file(filename, audio_array, sample_rate=24000, format='WAV', subtype='PCM_16', output_dir=None): |
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if output_dir: |
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os.makedirs(output_dir, exist_ok=True) |
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filepath = os.path.join(output_dir, filename) |
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else: |
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filepath = filename |
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i = 1 |
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name, ext = os.path.splitext(filepath) |
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while os.path.exists(filepath): |
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filepath = f"{name}_{i}{ext}" |
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i += 1 |
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sf.write(filepath, audio_array, sample_rate, format=format, subtype=subtype) |
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print(f"Saved audio to {filepath}") |
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def gen_and_save_audio(text_prompt, history_prompt=None, text_temp=0.7, waveform_temp=0.7, filename="", output_dir="bark_samples"): |
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def generate_unique_filename(base_filename): |
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name, ext = os.path.splitext(base_filename) |
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unique_filename = base_filename |
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counter = 1 |
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while os.path.exists(unique_filename): |
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unique_filename = f"{name}_{counter}{ext}" |
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counter += 1 |
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return unique_filename |
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longer_than_14_seconds, estimated_time = estimate_spoken_time(text_prompt) |
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print(f"Estimated time: {estimated_time:.2f} seconds.") |
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if longer_than_14_seconds: |
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print(f"Text Prompt could be too long, might want to try a shorter one if you get a bad result.") |
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print(f"Generating: {text_prompt}") |
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if args.history_prompt: |
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print(f"Using speaker: {history_prompt}") |
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else: |
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print(f"No speaker. Randomly generating a speaker.") |
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audio_array = generate_audio(text_prompt, history_prompt, text_temp=text_temp, |
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waveform_temp=waveform_temp) |
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if not filename: |
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date_str = datetime.datetime.now().strftime("%Y-%m-%d-%H") |
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truncated_text = text_prompt.replace("WOMAN:", "").replace("MAN:", "")[:15].strip().replace(" ", "_") |
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filename = f"{truncated_text}-history_prompt-{history_prompt}-text_temp-{text_temp}-waveform_temp-{waveform_temp}-{date_str}.wav" |
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filename = generate_unique_filename(filename) |
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save_audio_to_file(filename, audio_array, SAMPLE_RATE, output_dir=output_dir) |
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def print_speakers_list(): |
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print("Available history prompts:") |
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print("\nNon-specific speakers:") |
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print(" announcer") |
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print(" speaker_0 to speaker_9") |
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print("\nLanguage-specific speakers:") |
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for language, lang_code in SUPPORTED_LANGS: |
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speakers = ", ".join([f"{lang_code}_speaker_{n}" for n in range(10)]) |
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print(f"\n {language}({lang_code}):\n{speakers}") |
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text_prompts = [] |
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text_prompt = """ |
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In the beginning the Universe was created. This has made a lot of people very angry and been widely regarded as a bad move. |
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""" |
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text_prompts.append(text_prompt) |
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text_prompt = """ |
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A common mistake that people make when trying to design something completely foolproof is to underestimate the ingenuity of complete fools. |
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""" |
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text_prompts.append(text_prompt) |
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def main(args): |
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if args.list_speakers: |
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print_speakers_list() |
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else: |
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if args.text_prompt: |
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text_prompts_to_process = [args.text_prompt] |
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else: |
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print("No text prompt provided. Using default prompts defined in this file.") |
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text_prompts_to_process = text_prompts |
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if args.history_prompt: |
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history_prompt = args.history_prompt |
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else: |
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history_prompt = None |
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text_temp = args.text_temp if args.text_temp else 0.7 |
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waveform_temp = args.waveform_temp if args.waveform_temp else 0.7 |
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filename = args.filename if args.filename else "" |
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output_dir = args.output_dir if args.output_dir else "bark_samples" |
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print("Loading Bark models...") |
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if args.use_smaller_models: |
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print("Using smaller models.") |
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preload_models(use_smaller_models=True) |
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else: |
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preload_models() |
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print("Models loaded.") |
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for prompt in text_prompts_to_process: |
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gen_and_save_audio(prompt, history_prompt, text_temp, waveform_temp, filename, output_dir) |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser(description=""" |
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Generate and save audio. |
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install this first: pip install soundfile |
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Example: python bark_speak.py --text_prompt "It is a mistake to think you can solve any major problems just with potatoes." --history_prompt en_speaker_3 |
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""", formatter_class=argparse.RawTextHelpFormatter) |
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parser.add_argument("--text_prompt", help="Text prompt. If not provided, a set of default prompts will be used defined in this file.") |
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parser.add_argument("--history_prompt", help="Optional. Choose a speaker from the list of languages: " + ", ".join([lang[0] for lang in SUPPORTED_LANGS]) + ". Use --list_speakers to see all available options.") |
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parser.add_argument("--text_temp", type=float, help="Text temperature. Default is 0.7.") |
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parser.add_argument("--waveform_temp", type=float, help="Waveform temperature. Default is 0.7.") |
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parser.add_argument("--filename", help="Output filename. If not provided, a unique filename will be generated based on the text prompt and other parameters.") |
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parser.add_argument("--output_dir", help="Output directory. Default is 'bark_samples'.") |
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parser.add_argument("--list_speakers", action="store_true", help="List all preset speaker options instead of generating audio.") |
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parser.add_argument("--use_smaller_models", action="store_true", help="Use for GPUS with less than 10GB of memory, or for more speed.") |
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args = parser.parse_args() |
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main(args) |
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