while run demo_part3.ipynb, ascii codec error occrued

[dhvms99]

I run code below

from melo.api import TTS

texts = {
    'EN_NEWEST': "Did you ever hear a folk tale about a giant turtle?",  # The newest English base speaker model
    'EN': "Did you ever hear a folk tale about a giant turtle?",
    'ES': "El resplandor del sol acaricia las olas, pintando el cielo con una paleta deslumbrante.",
    'FR': "La lueur doree du soleil caresse les vagues, peignant le ciel d'une palette eblouissante.",
    'ZH': "在这次vacation中，我们计划去Paris欣赏埃菲尔铁塔和卢浮宫的美景。",
    'JP': "彼は毎朝ジョギングをして体を健康に保っています。",
    'KR': "안녕하세요! 오늘은 날씨가 정말 좋네요.",
}


src_path = f'{output_dir}/tmp.wav'

# Speed is adjustable
speed = 1.0

for language, text in texts.items():
    model = TTS(language=language, device=device)
    speaker_ids = model.hps.data.spk2id
    
    for speaker_key in speaker_ids.keys():
        speaker_id = speaker_ids[speaker_key]
        speaker_key = speaker_key.lower().replace('_', '-')
        
        source_se = torch.load(f'checkpoints_v2/base_speakers/ses/{speaker_key}.pth', map_location=device)
        model.tts_to_file(text, speaker_id, src_path, speed=speed)
        save_path = f'{output_dir}/output_v2_{speaker_key}.wav'

        # Run the tone color converter
        encode_message = "@MyShell"
        tone_color_converter.convert(
            audio_src_path=src_path, 
            src_se=source_se, 
            tgt_se=target_se, 
            output_path=save_path,
            message=encode_message)

and error occrued like below

{
	"name": "UnicodeEncodeError",
	"message": "'ascii' codec can't encode characters in position 12-13: ordinal not in range(128)",
	"stack": "---------------------------------------------------------------------------
UnicodeEncodeError                        Traceback (most recent call last)
Cell In[10], line 28
     25 speaker_key = speaker_key.lower().replace('_', '-')
     27 source_se = torch.load(f'checkpoints_v2/base_speakers/ses/{speaker_key}.pth', map_location=device)
---> 28 model.tts_to_file(text, speaker_id, src_path, speed=speed)
     29 save_path = f'{output_dir}/output_v2_{speaker_key}.wav'
     31 # Run the tone color converter

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\api.py:100, in TTS.tts_to_file(self, text, speaker_id, output_path, sdp_ratio, noise_scale, noise_scale_w, speed, pbar, format, position, quiet)
     98     t = re.sub(r'([a-z])([A-Z])', r'\\1 \\2', t)
     99 device = self.device
--> 100 bert, ja_bert, phones, tones, lang_ids = utils.get_text_for_tts_infer(t, language, self.hps, device, self.symbol_to_id)
    101 with torch.no_grad():
    102     x_tst = phones.to(device).unsqueeze(0)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\utils.py:23, in get_text_for_tts_infer(text, language_str, hps, device, symbol_to_id)
     22 def get_text_for_tts_infer(text, language_str, hps, device, symbol_to_id=None):
---> 23     norm_text, phone, tone, word2ph = clean_text(text, language_str)
     24     phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str, symbol_to_id)
     26     if hps.data.add_blank:

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\cleaner.py:12, in clean_text(text, language)
     10 language_module = language_module_map[language]
     11 norm_text = language_module.text_normalize(text)
---> 12 phones, tones, word2ph = language_module.g2p(norm_text)
     13 return norm_text, phones, tones, word2ph

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\french.py:49, in g2p(text, pad_start_end, tokenized)
     47     phone_list = ['UNK']
     48 else:
---> 49     phone_list = list(filter(lambda p: p != \" \", fr_to_ipa.fr2ipa(w)))
     51 for ph in phone_list:
     52     phones.append(ph)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\fr_phonemizer\\fr_to_ipa.py:26, in fr2ipa(text)
     24 e = Gruut(language=\"fr-fr\", keep_puncs=True, keep_stress=True, use_espeak_phonemes=True)
     25 # text = french_cleaners(text)
---> 26 phonemes = e.phonemize(text, separator=\"\")
     27 # print(phonemes)
     28 phonemes = remove_consecutive_t(phonemes)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\fr_phonemizer\\base.py:132, in BasePhonemizer.phonemize(self, text, separator, language)
    130 phonemized = []
    131 for t in text:
--> 132     p = self._phonemize(t, separator)
    133     phonemized.append(p)
    134 phonemized = self._phonemize_postprocess(phonemized, punctuations)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\fr_phonemizer\\gruut_wrapper.py:110, in Gruut._phonemize(self, text, separator)
    109 def _phonemize(self, text, separator):
--> 110     return self.phonemize_gruut(text, separator, tie=False)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\melo\\text\\fr_phonemizer\\gruut_wrapper.py:77, in Gruut.phonemize_gruut(self, text, separator, tie)
     58 \"\"\"Convert input text to phonemes.
     59 
     60 Gruut phonemizes the given `str` by seperating each phoneme character with `separator`, even for characters
   (...)
     74         with '_'. This option requires espeak>=1.49. Default to False.
     75 \"\"\"
     76 ph_list = []
---> 77 for sentence in gruut.sentences(text, lang=self.language, espeak=self.use_espeak_phonemes):
     78     for word in sentence:
     79         if word.is_break:
     80             # Use actual character for break phoneme (e.g., comma)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\__init__.py:79, in sentences(text, lang, ssml, espeak, major_breaks, minor_breaks, punctuations, explicit_lang, phonemes, break_phonemes, pos, **process_args)
     76         _LOCAL.processors[model_prefix] = text_processor
     78 assert text_processor is not None
---> 79 graph, root = text_processor(text, lang=lang, ssml=ssml, **process_args)
     81 yield from text_processor.sentences(
     82     graph,
     83     root,
   (...)
     90     pos=pos,
     91 )

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\text_processor.py:440, in TextProcessor.__call__(self, *args, **kwargs)
    438 def __call__(self, *args, **kwargs):
    439     \"\"\"Processes text or SSML\"\"\"
--> 440     return self.process(*args, **kwargs)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\text_processor.py:1176, in TextProcessor.process(self, text, lang, ssml, pos, phonemize, post_process, add_speak_tag, detect_numbers, detect_currency, detect_dates, detect_times, verbalize_numbers, verbalize_currency, verbalize_dates, verbalize_times, max_passes)
   1172             sentence_words.append(word_node)
   1174 if sentence_words:
   1175     # Final sentence
-> 1176     process_sentence(sentence_words)
   1177     sentence_words = []
   1179 if post_process:
   1180     # Post-process sentences

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\text_processor.py:1099, in TextProcessor.process.<locals>.process_sentence(words)
   1097 pos_settings = self.get_settings(node.lang)
   1098 if pos_settings.get_parts_of_speech is not None:
-> 1099     pos_tags = pos_settings.get_parts_of_speech(
   1100         [word.text for word in words]
   1101     )
   1102     for word, pos_tag in zip(words, pos_tags):
   1103         word.pos = pos_tag

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\lang.py:858, in DelayedPartOfSpeechTagger.__call__(self, words)
    856 if self.tagger is None:
    857     _LOGGER.debug(\"Loading part of speech tagger from %s\", self.model_path)
--> 858     self.tagger = PartOfSpeechTagger(self.model_path, **self.tagger_args)
    860 assert self.tagger is not None
    861 return self.tagger(words)

File d:\\OneDrive\\바탕 화면\\정통부 AI프로젝트\\.venv2\\lib\\site-packages\\gruut\\pos.py:63, in PartOfSpeechTagger.__init__(self, crf_tagger, **kwargs)
     60 else:
     61     # Load model
     62     self.crf_tagger = pycrfsuite.Tagger()
---> 63     self.crf_tagger.open(str(crf_tagger))

File pycrfsuite/_pycrfsuite.pyx:572, in pycrfsuite._pycrfsuite.Tagger.open()

File <stringsource>:15, in string.from_py.__pyx_convert_string_from_py_std__in_string()

UnicodeEncodeError: 'ascii' codec can't encode characters in position 12-13: ordinal not in range(128)"
}

This problem has been driving me crazy for days
I also do '$env:PYTHONIOENCODING="UTF-8"' this but didn't work.
please help me