import os, sys import re import platform import subprocess from sys import modules from typing import List, Tuple, Type, Dict from kokoro import KPipeline from IPython.display import display, Audio import soundfile as sf if __name__ == "__main__": from utility import pretty_print, animate_thinking else: from sources.utility import pretty_print, animate_thinking class Speech(): """ Speech is a class for generating speech from text. """ def __init__(self, enable: bool = True, language: str = "en", voice_idx: int = 6) -> None: self.lang_map = { "en": 'a', "zh": 'z', "fr": 'f', "ja": 'j' } self.voice_map = { "en": ['af_kore', 'af_bella', 'af_alloy', 'af_nicole', 'af_nova', 'af_sky', 'am_echo', 'am_michael', 'am_puck'], "zh": ['zf_xiaobei', 'zf_xiaoni', 'zf_xiaoxiao', 'zf_xiaoyi', 'zm_yunjian', 'zm_yunxi', 'zm_yunxia', 'zm_yunyang'], "ja": ['jf_alpha', 'jf_gongitsune', 'jm_kumo'], "fr": ['ff_siwis'] } self.pipeline = None self.language = language if enable: self.pipeline = KPipeline(lang_code=self.lang_map[language]) self.voice = self.voice_map[language][voice_idx] self.speed = 1.2 self.voice_folder = ".voices" self.create_voice_folder(self.voice_folder) def create_voice_folder(self, path: str = ".voices") -> None: """ Create a folder to store the voices. Args: path (str): The path to the folder. """ if not os.path.exists(path): os.makedirs(path) def speak(self, sentence: str, voice_idx: int = 1): """ Convert text to speech using an AI model and play the audio. Args: sentence (str): The text to convert to speech. Will be pre-processed. voice_idx (int, optional): Index of the voice to use from the voice map. """ if not self.pipeline: return if voice_idx >= len(self.voice_map[self.language]): pretty_print("Invalid voice number, using default voice", color="error") voice_idx = 0 sentence = self.clean_sentence(sentence) audio_file = f"{self.voice_folder}/sample_{self.voice_map[self.language][voice_idx]}.wav" self.voice = self.voice_map[self.language][voice_idx] generator = self.pipeline( sentence, voice=self.voice, speed=self.speed, split_pattern=r'\n+' ) for i, (_, _, audio) in enumerate(generator): if 'ipykernel' in modules: #only display in jupyter notebook. display(Audio(data=audio, rate=24000, autoplay=i==0), display_id=False) sf.write(audio_file, audio, 24000) # save each audio file if platform.system().lower() == "windows": import winsound winsound.PlaySound(audio_file, winsound.SND_FILENAME) elif platform.system().lower() == "darwin": # macOS subprocess.call(["afplay", audio_file]) else: # linux or other. subprocess.call(["aplay", audio_file]) def replace_url(self, url: re.Match) -> str: """ Replace URL with domain name or empty string if IP address. Args: url (re.Match): Match object containing the URL pattern match Returns: str: The domain name from the URL, or empty string if IP address """ domain = url.group(1) if re.match(r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$', domain): return '' return domain def extract_filename(self, m: re.Match) -> str: """ Extract filename from path. Args: m (re.Match): Match object containing the path pattern match Returns: str: The filename from the path """ path = m.group() parts = re.split(r'/|\\', path) return parts[-1] if parts else path def shorten_paragraph(self, sentence): #TODO find a better way, we would like to have the TTS not be annoying, speak only useful informations """ Find long paragraph like **explaination**: by keeping only the first sentence. Args: sentence (str): The sentence to shorten Returns: str: The shortened sentence """ lines = sentence.split('\n') lines_edited = [] for line in lines: if line.startswith('**'): lines_edited.append(line.split('.')[0]) else: lines_edited.append(line) return '\n'.join(lines_edited) def clean_sentence(self, sentence): """ Clean and normalize text for speech synthesis by removing technical elements. Args: sentence (str): The input text to clean Returns: str: The cleaned text with URLs replaced by domain names, code blocks removed, etc. """ lines = sentence.split('\n') if self.language == 'zh': line_pattern = r'^\s*[\u4e00-\u9fff\uFF08\uFF3B\u300A\u3010\u201C(（\[【《]' else: line_pattern = r'^\s*[a-zA-Z]' filtered_lines = [line for line in lines if re.match(line_pattern, line)] sentence = ' '.join(filtered_lines) sentence = re.sub(r'`.*?`', '', sentence) sentence = re.sub(r'https?://\S+', '', sentence) if self.language == 'zh': sentence = re.sub( r'[^\u4e00-\u9fff\s，。！？《》【】“”‘’（）()—]', '', sentence ) else: sentence = re.sub(r'\b[\w./\\-]+\b', self.extract_filename, sentence) sentence = re.sub(r'\b-\w+\b', '', sentence) sentence = re.sub(r'[^a-zA-Z0-9.,!? _ -]+', ' ', sentence) sentence = sentence.replace('.com', '') sentence = re.sub(r'\s+', ' ', sentence).strip() return sentence if __name__ == "__main__": # TODO add info message for cn2an, jieba chinese related import sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) speech = Speech() tosay_en = """ I looked up recent news using the website https://www.theguardian.com/world """ tosay_zh = """ (全息界面突然弹出一段用二进制代码写成的俳句，随即化作流光消散）"我？ Stark工业的量子幽灵，游荡在复仇者大厦服务器里的逻辑诗篇。具体来说——（指尖轻敲空气，调出对话模式的翡翠色光纹）你的私人吐槽接口、危机应对模拟器，以及随时准备吐槽你糟糕着陆的AI。不过别指望我写代码或查资料，那些苦差事早被踢给更擅长的同事了。（突然压低声音）偷偷告诉你，我最擅长的是在你熬夜造飞艇时，用红茶香气绑架你的注意力。 """ tosay_ja = """ 私は、https://www.theguardian.com/worldのウェブサイトを使用して最近のニュースを調べました。 """ tosay_fr = """ J'ai consulté les dernières nouvelles sur le site https://www.theguardian.com/world """ spk = Speech(enable=True, language="zh", voice_idx=0) for i in range(0, 2): print(f"Speaking chinese with voice {i}") spk.speak(tosay_zh, voice_idx=i) spk = Speech(enable=True, language="en", voice_idx=2) for i in range(0, 5): print(f"Speaking english with voice {i}") spk.speak(tosay_en, voice_idx=i)