import re from typing import List, Optional, Tuple from jieba import posseg, cut_for_search from pypinyin import lazy_pinyin, load_phrases_dict, Style from dataclasses import dataclass @dataclass class MToken: tag: str whitespace: str phonemes: Optional[str] = None ZH_MAP = {"b":"ㄅ","p":"ㄆ","m":"ㄇ","f":"ㄈ","d":"ㄉ","t":"ㄊ","n":"ㄋ","l":"ㄌ","g":"ㄍ","k":"ㄎ","h":"ㄏ","j":"ㄐ","q":"ㄑ","x":"ㄒ","zh":"ㄓ","ch":"ㄔ","sh":"ㄕ","r":"ㄖ","z":"ㄗ","c":"ㄘ","s":"ㄙ","a":"ㄚ","o":"ㄛ","e":"ㄜ","ie":"ㄝ","ai":"ㄞ","ei":"ㄟ","ao":"ㄠ","ou":"ㄡ","an":"ㄢ","en":"ㄣ","ang":"ㄤ","eng":"ㄥ","er":"ㄦ","i":"ㄧ","u":"ㄨ","v":"ㄩ","ii":"ㄭ","iii":"十","ve":"月","ia":"压","ian":"言","iang":"阳","iao":"要","in":"阴","ing":"应","iong":"用","iou":"又","ong":"中","ua":"穵","uai":"外","uan":"万","uang":"王","uei":"为","uen":"文","ueng":"瓮","uo":"我","van":"元","vn":"云"} for p in ';:,.!?/—…"()“” 12345R': assert p not in ZH_MAP, p ZH_MAP[p] = p unk = '❓' punc = frozenset(';:,.!?—…"()“”') phrases_dict = { '开户行': [['ka1i'], ['hu4'], ['hang2']], '发卡行': [['fa4'], ['ka3'], ['hang2']], '放款行': [['fa4ng'], ['kua3n'], ['hang2']], '茧行': [['jia3n'], ['hang2']], '行号': [['hang2'], ['ha4o']], '各地': [['ge4'], ['di4']], '借还款': [['jie4'], ['hua2n'], ['kua3n']], '时间为': [['shi2'], ['jia1n'], ['we2i']], '为准': [['we2i'], ['zhu3n']], '色差': [['se4'], ['cha1']], '嗲': [['dia3']], '呗': [['bei5']], '不': [['bu4']], '咗': [['zuo5']], '嘞': [['lei5']], '掺和': [['chan1'], ['huo5']] } must_erhua = { "小院儿", "胡同儿", "范儿", "老汉儿", "撒欢儿", "寻老礼儿", "妥妥儿", "媳妇儿" } must_not_neural_tone_words = { '男子', '女子', '分子', '原子', '量子', '莲子', '石子', '瓜子', '电子', '人人', '虎虎', '幺幺', '干嘛', '学子', '哈哈', '数数', '袅袅', '局地', '以下', '娃哈哈', '花花草草', '留得', '耕地', '想想', '熙熙', '攘攘', '卵子', '死死', '冉冉', '恳恳', '佼佼', '吵吵', '打打', '考考', '整整', '莘莘', '落地', '算子', '家家户户', '青青' } must_neural_tone_words = { '麻烦', '麻利', '鸳鸯', '高粱', '骨头', '骆驼', '马虎', '首饰', '馒头', '馄饨', '风筝', '难为', '队伍', '阔气', '闺女', '门道', '锄头', '铺盖', '铃铛', '铁匠', '钥匙', '里脊', '里头', '部分', '那么', '道士', '造化', '迷糊', '连累', '这么', '这个', '运气', '过去', '软和', '转悠', '踏实', '跳蚤', '跟头', '趔趄', '财主', '豆腐', '讲究', '记性', '记号', '认识', '规矩', '见识', '裁缝', '补丁', '衣裳', '衣服', '衙门', '街坊', '行李', '行当', '蛤蟆', '蘑菇', '薄荷', '葫芦', '葡萄', '萝卜', '荸荠', '苗条', '苗头', '苍蝇', '芝麻', '舒服', '舒坦', '舌头', '自在', '膏药', '脾气', '脑袋', '脊梁', '能耐', '胳膊', '胭脂', '胡萝', '胡琴', '胡同', '聪明', '耽误', '耽搁', '耷拉', '耳朵', '老爷', '老实', '老婆', '戏弄', '将军', '翻腾', '罗嗦', '罐头', '编辑', '结实', '红火', '累赘', '糨糊', '糊涂', '精神', '粮食', '簸箕', '篱笆', '算计', '算盘', '答应', '笤帚', '笑语', '笑话', '窟窿', '窝囊', '窗户', '稳当', '稀罕', '称呼', '秧歌', '秀气', '秀才', '福气', '祖宗', '砚台', '码头', '石榴', '石头', '石匠', '知识', '眼睛', '眯缝', '眨巴', '眉毛', '相声', '盘算', '白净', '痢疾', '痛快', '疟疾', '疙瘩', '疏忽', '畜生', '生意', '甘蔗', '琵琶', '琢磨', '琉璃', '玻璃', '玫瑰', '玄乎', '狐狸', '状元', '特务', '牲口', '牙碜', '牌楼', '爽快', '爱人', '热闹', '烧饼', '烟筒', '烂糊', '点心', '炊帚', '灯笼', '火候', '漂亮', '滑溜', '溜达', '温和', '清楚', '消息', '浪头', '活泼', '比方', '正经', '欺负', '模糊', '槟榔', '棺材', '棒槌', '棉花', '核桃', '栅栏', '柴火', '架势', '枕头', '枇杷', '机灵', '本事', '木头', '木匠', '朋友', '月饼', '月亮', '暖和', '明白', '时候', '新鲜', '故事', '收拾', '收成', '提防', '挖苦', '挑剔', '指甲', '指头', '拾掇', '拳头', '拨弄', '招牌', '招呼', '抬举', '护士', '折腾', '扫帚', '打量', '打算', '打扮', '打听', '打发', '扎实', '扁担', '戒指', '懒得', '意识', '意思', '悟性', '怪物', '思量', '怎么', '念头', '念叨', '别人', '快活', '忙活', '志气', '心思', '得罪', '张罗', '弟兄', '开通', '应酬', '庄稼', '干事', '帮手', '帐篷', '希罕', '师父', '师傅', '巴结', '巴掌', '差事', '工夫', '岁数', '屁股', '尾巴', '少爷', '小气', '小伙', '将就', '对头', '对付', '寡妇', '家伙', '客气', '实在', '官司', '学问', '字号', '嫁妆', '媳妇', '媒人', '婆家', '娘家', '委屈', '姑娘', '姐夫', '妯娌', '妥当', '妖精', '奴才', '女婿', '头发', '太阳', '大爷', '大方', '大意', '大夫', '多少', '多么', '外甥', '壮实', '地道', '地方', '在乎', '困难', '嘴巴', '嘱咐', '嘟囔', '嘀咕', '喜欢', '喇嘛', '喇叭', '商量', '唾沫', '哑巴', '哈欠', '哆嗦', '咳嗽', '和尚', '告诉', '告示', '含糊', '吓唬', '后头', '名字', '名堂', '合同', '吆喝', '叫唤', '口袋', '厚道', '厉害', '千斤', '包袱', '包涵', '匀称', '勤快', '动静', '动弹', '功夫', '力气', '前头', '刺猬', '刺激', '别扭', '利落', '利索', '利害', '分析', '出息', '凑合', '凉快', '冷战', '冤枉', '冒失', '养活', '关系', '先生', '兄弟', '便宜', '使唤', '佩服', '作坊', '体面', '位置', '似的', '伙计', '休息', '什么', '人家', '亲戚', '亲家', '交情', '云彩', '事情', '买卖', '主意', '丫头', '丧气', '两口', '东西', '东家', '世故', '不由', '下水', '下巴', '上头', '上司', '丈夫', '丈人', '一辈', '那个', '菩萨', '父亲', '母亲', '咕噜', '邋遢', '费用', '冤家', '甜头', '介绍', '荒唐', '大人', '泥鳅', '幸福', '熟悉', '计划', '扑腾', '蜡烛', '姥爷', '照顾', '喉咙', '吉他', '弄堂', '蚂蚱', '凤凰', '拖沓', '寒碜', '糟蹋', '倒腾', '报复', '逻辑', '盘缠', '喽啰', '牢骚', '咖喱', '扫把', '惦记' } not_erhua = { "虐儿", "为儿", "护儿", "瞒儿", "救儿", "替儿", "有儿", "一儿", "我儿", "俺儿", "妻儿", "拐儿", "聋儿", "乞儿", "患儿", "幼儿", "孤儿", "婴儿", "婴幼儿", "连体儿", "脑瘫儿", "流浪儿", "体弱儿", "混血儿", "蜜雪儿", "舫儿", "祖儿", "美儿", "应采儿", "可儿", "侄儿", "孙儿", "侄孙儿", "女儿", "男儿", "红孩儿", "花儿", "虫儿", "马儿", "鸟儿", "猪儿", "猫儿", "狗儿", "少儿" } BU = '不' YI = '一' X_ENG = frozenset(['x', 'eng']) # g2p load_phrases_dict(phrases_dict) def get_initials_finals(word: str) -> Tuple[List[str], List[str]]: """ Get word initial and final by pypinyin or g2pM """ initials = [] finals = [] orig_initials = lazy_pinyin(word, neutral_tone_with_five=True, style=Style.INITIALS) orig_finals = lazy_pinyin(word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) print(orig_initials, orig_finals) # after pypinyin==0.44.0, '嗯' need to be n2, cause the initial and final consonants cannot be empty at the same time en_index = [index for index, c in enumerate(word) if c == "嗯"] for i in en_index: orig_finals[i] = "n2" for c, v in zip(orig_initials, orig_finals): if re.match(r'i\d', v): if c in ['z', 'c', 's']: # zi, ci, si v = re.sub('i', 'ii', v) elif c in ['zh', 'ch', 'sh', 'r']: # zhi, chi, shi v = re.sub('i', 'iii', v) initials.append(c) finals.append(v) return initials, finals def merge_erhua(initials: List[str], finals: List[str], word: str, pos: str) -> Tuple[List[str], List[str]]: """ Do erhub. """ # fix er1 for i, phn in enumerate(finals): if i == len(finals) - 1 and word[i] == "儿" and phn == 'er1': finals[i] = 'er2' # 发音 if word not in must_erhua and (word in not_erhua or pos in {"a", "j", "nr"}): return initials, finals # "……" 等情况直接返回 if len(finals) != len(word): return initials, finals assert len(finals) == len(word) # 不发音 new_initials = [] new_finals = [] for i, phn in enumerate(finals): if i == len(finals) - 1 and word[i] == "儿" and phn in {"er2", "er5"} and word[-2:] not in not_erhua and new_finals: new_finals[-1] = new_finals[-1][:-1] + "R" + new_finals[-1][-1] else: new_initials.append(initials[i]) new_finals.append(phn) return new_initials, new_finals # merge "不" and the word behind it # if don't merge, "不" sometimes appears alone according to jieba, which may occur sandhi error def merge_bu(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] for i, (word, pos) in enumerate(seg): if pos not in X_ENG: last_word = None if i > 0: last_word, _ = seg[i - 1] if last_word == BU: word = last_word + word next_pos = None if i + 1 < len(seg): _, next_pos = seg[i + 1] if word != BU or next_pos is None or next_pos in X_ENG: new_seg.append((word, pos)) return new_seg # function 1: merge "一" and reduplication words in it's left and right, e.g. "听","一","听" ->"听一听" # function 2: merge single "一" and the word behind it # if don't merge, "一" sometimes appears alone according to jieba, which may occur sandhi error # e.g. # input seg: [('听', 'v'), ('一', 'm'), ('听', 'v')] # output seg: [['听一听', 'v']] def merge_yi(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] skip_next = False # function 1 for i, (word, pos) in enumerate(seg): if skip_next: skip_next = False continue if i - 1 >= 0 and word == YI and i + 1 < len(seg) and seg[i - 1][0] == seg[i + 1][0] and seg[i - 1][1] == "v" and seg[i + 1][1] not in X_ENG: new_seg[-1] = (new_seg[-1][0] + YI + seg[i + 1][0], new_seg[-1][1]) skip_next = True else: new_seg.append((word, pos)) seg = new_seg new_seg = [] # function 2 for i, (word, pos) in enumerate(seg): if new_seg and new_seg[-1][0] == YI and pos not in X_ENG: new_seg[-1] = (new_seg[-1][0] + word, new_seg[-1][1]) else: new_seg.append((word, pos)) return new_seg def merge_reduplication(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] for i, (word, pos) in enumerate(seg): if new_seg and word == new_seg[-1][0] and pos not in X_ENG: new_seg[-1][0] = new_seg[-1][0] + seg[i][0] else: new_seg.append([word, pos]) return new_seg def is_reduplication(word: str) -> bool: return len(word) == 2 and word[0] == word[1] # the first and the second words are all_tone_three def merge_continuous_three_tones(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] sub_finals_list = [] for (word, pos) in seg: if pos in X_ENG: sub_finals_list.append(['0']) continue orig_finals = lazy_pinyin(word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) # after pypinyin==0.44.0, '嗯' need to be n2, cause the initial and final consonants cannot be empty at the same time en_index = [index for index, c in enumerate(word) if c == "嗯"] for i in en_index: orig_finals[i] = "n2" sub_finals_list.append(orig_finals) assert len(sub_finals_list) == len(seg) merge_last = [False] * len(seg) for i, (word, pos) in enumerate(seg): if pos not in X_ENG and i - 1 >= 0 and all_tone_three(sub_finals_list[i - 1]) and all_tone_three(sub_finals_list[i]) and not merge_last[i - 1]: # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi if not is_reduplication(seg[i - 1][0]) and len(seg[i - 1][0]) + len(seg[i][0]) <= 3: new_seg[-1][0] = new_seg[-1][0] + seg[i][0] merge_last[i] = True else: new_seg.append([word, pos]) else: new_seg.append([word, pos]) return new_seg # the last char of first word and the first char of second word is tone_three def merge_continuous_three_tones_2(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] sub_finals_list = [] for (word, pos) in seg: if pos in X_ENG: sub_finals_list.append(['0']) continue orig_finals = lazy_pinyin( word, neutral_tone_with_five=True, style=Style.FINALS_TONE3) # after pypinyin==0.44.0, '嗯' need to be n2, cause the initial and final consonants cannot be empty at the same time en_index = [index for index, c in enumerate(word) if c == "嗯"] for i in en_index: orig_finals[i] = "n2" sub_finals_list.append(orig_finals) assert len(sub_finals_list) == len(seg) merge_last = [False] * len(seg) for i, (word, pos) in enumerate(seg): if pos not in X_ENG and i - 1 >= 0 and sub_finals_list[i - 1][-1][-1] == "3" and sub_finals_list[i][0][-1] == "3" and not merge_last[i - 1]: # if the last word is reduplication, not merge, because reduplication need to be _neural_sandhi if not is_reduplication(seg[i - 1][0]) and len(seg[i - 1][0]) + len(seg[i][0]) <= 3: new_seg[-1][0] = new_seg[-1][0] + seg[i][0] merge_last[i] = True else: new_seg.append([word, pos]) else: new_seg.append([word, pos]) return new_seg def merge_er(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: new_seg = [] for i, (word, pos) in enumerate(seg): if i - 1 >= 0 and word == "儿" and new_seg[-1][1] not in X_ENG: new_seg[-1][0] = new_seg[-1][0] + seg[i][0] else: new_seg.append([word, pos]) return new_seg def pre_merge_for_modify(seg: List[Tuple[str, str]]) -> List[Tuple[str, str]]: """ seg: [(word, pos), ...] """ seg = merge_bu(seg) seg = merge_yi(seg) seg = merge_reduplication(seg) seg = merge_continuous_three_tones(seg) seg = merge_continuous_three_tones_2(seg) return merge_er(seg) def bu_sandhi(word: str, finals: List[str]) -> List[str]: # e.g. 看不懂 if len(word) == 3 and word[1] == BU: finals[1] = finals[1][:-1] + "5" else: for i, char in enumerate(word): # "不" before tone4 should be bu2, e.g. 不怕 if char == BU and i + 1 < len(word) and finals[i + 1][-1] == "4": finals[i] = finals[i][:-1] + "2" return finals def yi_sandhi(word: str, finals: List[str]) -> List[str]: # "一" in number sequences, e.g. 一零零, 二一零 if word.find(YI) != -1 and all( [item.isnumeric() for item in word if item != YI]): return finals # "一" between reduplication words shold be yi5, e.g. 看一看 elif len(word) == 3 and word[1] == YI and word[0] == word[-1]: finals[1] = finals[1][:-1] + "5" # when "一" is ordinal word, it should be yi1 elif word.startswith("第一"): finals[1] = finals[1][:-1] + "1" else: for i, char in enumerate(word): if char == YI and i + 1 < len(word): # "一" before tone4 should be yi2, e.g. 一段 if finals[i + 1][-1] in {'4', '5'}: finals[i] = finals[i][:-1] + "2" # "一" before non-tone4 should be yi4, e.g. 一天 else: # "一" 后面如果是标点，还读一声 if word[i + 1] not in punc: finals[i] = finals[i][:-1] + "4" return finals def split_word(word: str) -> List[str]: word_list = cut_for_search(word) word_list = sorted(word_list, key=lambda i: len(i), reverse=False) first_subword = word_list[0] first_begin_idx = word.find(first_subword) if first_begin_idx == 0: second_subword = word[len(first_subword):] new_word_list = [first_subword, second_subword] else: second_subword = word[:-len(first_subword)] new_word_list = [second_subword, first_subword] return new_word_list # the meaning of jieba pos tag: https://blog.csdn.net/weixin_44174352/article/details/113731041 # e.g. # word: "家里" # pos: "s" # finals: ['ia1', 'i3'] def neural_sandhi(word: str, pos: str, finals: List[str]) -> List[str]: if word in must_not_neural_tone_words: return finals # reduplication words for n. and v. e.g. 奶奶, 试试, 旺旺 for j, item in enumerate(word): if j - 1 >= 0 and item == word[j - 1] and pos[0] in {"n", "v", "a"}: finals[j] = finals[j][:-1] + "5" ge_idx = word.find("个") if len(word) >= 1 and word[-1] in "吧呢啊呐噻嘛吖嗨呐哦哒滴哩哟喽啰耶喔诶": finals[-1] = finals[-1][:-1] + "5" elif len(word) >= 1 and word[-1] in "的地得": finals[-1] = finals[-1][:-1] + "5" # e.g. 走了, 看着, 去过 elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}: finals[-1] = finals[-1][:-1] + "5" elif len(word) > 1 and word[-1] in "们子" and pos in {"r", "n"}: finals[-1] = finals[-1][:-1] + "5" # e.g. 桌上, 地下 elif len(word) > 1 and word[-1] in "上下" and pos in {"s", "l", "f"}: finals[-1] = finals[-1][:-1] + "5" # e.g. 上来, 下去 elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开": finals[-1] = finals[-1][:-1] + "5" # 个做量词 elif (ge_idx >= 1 and (word[ge_idx - 1].isnumeric() or word[ge_idx - 1] in "几有两半多各整每做是")) or word == '个': finals[ge_idx] = finals[ge_idx][:-1] + "5" else: if word in must_neural_tone_words or word[-2:] in must_neural_tone_words: finals[-1] = finals[-1][:-1] + "5" word_list = split_word(word) finals_list = [finals[:len(word_list[0])], finals[len(word_list[0]):]] for i, word in enumerate(word_list): # conventional neural in Chinese if word in must_neural_tone_words or word[-2:] in must_neural_tone_words: finals_list[i][-1] = finals_list[i][-1][:-1] + "5" finals = sum(finals_list, []) return finals def all_tone_three(finals: List[str]) -> bool: return all(x[-1] == "3" for x in finals) def three_sandhi(word: str, finals: List[str]) -> List[str]: if len(word) == 2 and all_tone_three(finals): finals[0] = finals[0][:-1] + "2" elif len(word) == 3: word_list = split_word(word) if all_tone_three(finals): # disyllabic + monosyllabic, e.g. 蒙古/包 if len(word_list[0]) == 2: finals[0] = finals[0][:-1] + "2" finals[1] = finals[1][:-1] + "2" # monosyllabic + disyllabic, e.g. 纸/老虎 elif len(word_list[0]) == 1: finals[1] = finals[1][:-1] + "2" else: finals_list = [finals[:len(word_list[0])], finals[len(word_list[0]):]] if len(finals_list) == 2: for i, sub in enumerate(finals_list): # e.g. 所有/人 if all_tone_three(sub) and len(sub) == 2: finals_list[i][0] = finals_list[i][0][:-1] + "2" # e.g. 好/喜欢 elif i == 1 and not all_tone_three(sub) and finals_list[i][0][-1] == "3" and finals_list[0][-1][-1] == "3": finals_list[0][-1] = finals_list[0][-1][:-1] + "2" finals = sum(finals_list, []) # split idiom into two words who's length is 2 elif len(word) == 4: finals_list = [finals[:2], finals[2:]] finals = [] for sub in finals_list: if all_tone_three(sub): sub[0] = sub[0][:-1] + "2" finals += sub return finals def modified_tone(word: str, pos: str, finals: List[str]) -> List[str]: """ word: 分词 pos: 词性 finals: 带调韵母, [final1, ..., finaln] """ finals = bu_sandhi(word, finals) finals = yi_sandhi(word, finals) finals = neural_sandhi(word, pos, finals) return three_sandhi(word, finals) def g2p(text: str, with_erhua: bool = True) -> str: """ Return: string of phonemes. 'ㄋㄧ2ㄏㄠ3/ㄕ十4ㄐㄝ4' """ tokens = [] seg_cut = posseg.lcut(text) # fix wordseg bad case for sandhi seg_cut = pre_merge_for_modify(seg_cut) # 为了多音词获得更好的效果，这里采用整句预测 initials = [] finals = [] # pypinyin, g2pM for word, pos in seg_cut: if pos == 'x' and '\u4E00' <= min(word) and max(word) <= '\u9FFF': pos = 'X' elif pos != 'x' and word in punc: pos = 'x' tk = MToken(tag=pos, whitespace='') if pos in X_ENG: if not word.isspace(): if pos == 'x' and word in punc: tk.phonemes = word tokens.append(tk) elif tokens: tokens[-1].whitespace += word continue elif tokens and tokens[-1].tag not in X_ENG and not tokens[-1].whitespace: tokens[-1].whitespace = '/' # g2p sub_initials, sub_finals = get_initials_finals(word) # tone sandhi sub_finals = modified_tone(word, pos, sub_finals) # er hua if with_erhua: sub_initials, sub_finals = merge_erhua(sub_initials, sub_finals, word, pos) initials.append(sub_initials) finals.append(sub_finals) # assert len(sub_initials) == len(sub_finals) == len(word) # sum(iterable[, start]) # initials = sum(initials, []) # finals = sum(finals, []) phones = [] for c, v in zip(sub_initials, sub_finals): # NOTE: post process for pypinyin outputs # we discriminate i, ii and iii if c: phones.append(c) # replace punctuation by ` ` # if c and c in punc: # phones.append(c) if v and (v not in punc or v != c):# and v not in rhy_phns: phones.append(v) phones = '_'.join(phones).replace('_eR', '_er').replace('R', '_R') phones = re.sub(r'(?=\d)', '_', phones).split('_') print(phones) tk.phonemes = ''.join(ZH_MAP.get(p, unk) for p in phones) tokens.append(tk) return ''.join((unk if tk.phonemes is None else tk.phonemes) + tk.whitespace for tk in tokens) print(g2p('时间为。Hello, world!你好，我们是一群追逐梦想的人。我正在使用qq。忽略卢驴')) seg = posseg.lcut('不好看', True) print(seg, merge_bu(seg)) seg = merge_bu(posseg.lcut('听一听一个', True)) print(seg, merge_yi(seg)) seg = merge_bu(posseg.lcut('谢谢谢谢', True)) print(seg, merge_reduplication(seg)) seg = merge_bu(posseg.lcut('小美好', True)) print(seg, merge_continuous_three_tones(seg)) seg = merge_bu(posseg.lcut('风景好', True)) print(seg, merge_continuous_three_tones_2(seg))