diff --git a/tiny_tts/text/english.py b/tiny_tts/text/english.py
deleted file mode 100644
index 1a57743..0000000
--- a/tiny_tts/text/english.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import pickle
-import os
-import re
-from g2p_en import G2p
-
-from . import symbols
-
-from .english_utils.abbreviations import expand_abbreviations
-from .english_utils.time_norm import expand_time_english
-from .english_utils.number_norm import normalize_numbers
-
-
-def distribute_phone(n_phone, n_word):
-    phones_per_word = [0] * n_word
-    for task in range(n_phone):
-        min_tasks = min(phones_per_word)
-        min_indices = [
-            i for i, x in enumerate(phones_per_word) if x == min_tasks
-        ]
-        chosen_index = min_indices[len(min_indices) // 2]
-        phones_per_word[chosen_index] += 1
-    return phones_per_word
-
-
-from transformers import AutoTokenizer
-
-current_file_path = os.path.dirname(__file__)
-CMU_DICT_PATH = os.path.join(current_file_path, "cmudict.rep")
-CACHE_PATH = os.path.join(current_file_path, "cmudict_cache.pickle")
-_g2p = G2p()
-
-arpa = {
-    "AH0", "S", "AH1", "EY2", "AE2", "EH0", "OW2", "UH0", "NG", "B",
-    "G", "AY0", "M", "AA0", "F", "AO0", "ER2", "UH1", "IY1", "AH2",
-    "DH", "IY0", "EY1", "IH0", "K", "N", "W", "IY2", "T", "AA1",
-    "ER1", "EH2", "OY0", "UH2", "UW1", "Z", "AW2", "AW1", "V", "UW2",
-    "AA2", "ER", "AW0", "UW0", "R", "OW1", "EH1", "ZH", "AE0", "IH2",
-    "IH", "Y", "JH", "P", "AY1", "EY0", "OY2", "TH", "HH", "D",
-    "ER0", "CH", "AO1", "AE1", "AO2", "OY1", "AY2", "IH1", "OW0", "L", "SH",
-}
-
-
-def map_phoneme(ph):
-    rep_map = {
-        "：": ",", "；": ",", "，": ",", "。": ".", "！": "!",
-        "？": "?", "\n": ".", "·": ",", "、": ",", "...": "…", "v": "V",
-    }
-    if ph in rep_map.keys():
-        ph = rep_map[ph]
-    if ph in symbols:
-        return ph
-    if ph not in symbols:
-        ph = "UNK"
-    return ph
-
-
-def read_dict():
-    g2p_dict = {}
-    start_line = 49
-    with open(CMU_DICT_PATH) as f:
-        line = f.readline()
-        line_index = 1
-        while line:
-            if line_index >= start_line:
-                line = line.strip()
-                word_split = line.split("  ")
-                word = word_split[0]
-
-                syllable_split = word_split[1].split(" - ")
-                g2p_dict[word] = []
-                for syllable in syllable_split:
-                    phone_split = syllable.split(" ")
-                    g2p_dict[word].append(phone_split)
-
-            line_index = line_index + 1
-            line = f.readline()
-
-    return g2p_dict
-
-
-def cache_dict(g2p_dict, file_path):
-    with open(file_path, "wb") as pickle_file:
-        pickle.dump(g2p_dict, pickle_file)
-
-
-def get_dict():
-    if os.path.exists(CACHE_PATH):
-        with open(CACHE_PATH, "rb") as pickle_file:
-            g2p_dict = pickle.load(pickle_file)
-    else:
-        g2p_dict = read_dict()
-        cache_dict(g2p_dict, CACHE_PATH)
-
-    return g2p_dict
-
-
-eng_dict = get_dict()
-
-
-def parse_phoneme(phn):
-    tone = 0
-    if re.search(r"\d$", phn):
-        tone = int(phn[-1]) + 1
-        phn = phn[:-1]
-    return phn.lower(), tone
-
-
-def parse_syllables(syllables):
-    tones = []
-    phonemes = []
-    for phn_list in syllables:
-        for i in range(len(phn_list)):
-            phn = phn_list[i]
-            phn, tone = parse_phoneme(phn)
-            phonemes.append(phn)
-            tones.append(tone)
-    return phonemes, tones
-
-
-def normalize_text(text):
-    text = text.lower()
-    text = expand_time_english(text)
-    text = normalize_numbers(text)
-    text = expand_abbreviations(text)
-    return text
-
-
-model_id = 'bert-base-uncased'
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-
-
-def grapheme_to_phoneme(text, pad_start_end=True, tokenized=None):
-    if tokenized is None:
-        tokenized = tokenizer.tokenize(text)
-    ph_groups = []
-    for t in tokenized:
-        if not t.startswith("#"):
-            ph_groups.append([t])
-        else:
-            ph_groups[-1].append(t.replace("#", ""))
-
-    phones = []
-    tones = []
-    word2ph = []
-    for group in ph_groups:
-        w = "".join(group)
-        phone_len = 0
-        word_len = len(group)
-        if w.upper() in eng_dict:
-            phns, tns = parse_syllables(eng_dict[w.upper()])
-            phones += phns
-            tones += tns
-            phone_len += len(phns)
-        else:
-            phone_list = list(filter(lambda p: p != " ", _g2p(w)))
-            for ph in phone_list:
-                if ph in arpa:
-                    ph, tn = parse_phoneme(ph)
-                    phones.append(ph)
-                    tones.append(tn)
-                else:
-                    phones.append(ph)
-                    tones.append(0)
-                phone_len += 1
-        aaa = distribute_phone(phone_len, word_len)
-        word2ph += aaa
-    phones = [map_phoneme(i) for i in phones]
-
-    if pad_start_end:
-        phones = ["_"] + phones + ["_"]
-        tones = [0] + tones + [0]
-        word2ph = [1] + word2ph + [1]
-    return phones, tones, word2ph