使用g2p时安装依赖关系_taggers/averaged_perceptron_tagger.zip

在使用g2p时安装依赖关系 “averaged_perceptron_tagger” “cmudict”

https://github.com/Kyubyong/g2p

运行 python -m nltk.downloader “averaged_perceptron_tagger” “cmudict”

输出：
[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data] /home/oppoer/nltk_data…
[nltk_data] Unzipping taggers/averaged_perceptron_tagger.zip.
[nltk_data] Downloading package cmudict to /home/oppoer/nltk_data…
[nltk_data] Unzipping corpora/cmudict.zip.
表示安装成功

测试：
from g2p_en import G2p

texts = [“I have $250 in my pocket.”, # number -> spell-out
“popular pets, e.g. cats and dogs”, # e.g. -> for example
“I refuse to collect the refuse around here.”, # homograph
“I’m an activationist.”] # newly coined word
g2p = G2p()
for text in texts:
out = g2p(text)
print(out)

输出：
[‘AY1’, ’ ', ‘HH’, ‘AE1’, ‘V’, ’ ', ‘T’, ‘UW1’, ’ ', ‘HH’, ‘AH1’, ‘N’, ‘D’, ‘R’, ‘AH0’, ‘D’, ’ ', ‘F’, ‘IH1’, ‘F’, ‘T’, ‘IY0’, ’ ', ‘D’, ‘AA1’, ‘L’, ‘ER0’, ‘Z’, ’ ', ‘IH0’, ‘N’, ’ ', ‘M’, ‘AY1’, ’ ', ‘P’, ‘AA1’, ‘K’, ‘AH0’, ‘T’, ’ ', ‘.’]
[‘P’, ‘AA1’, ‘P’, ‘Y’, ‘AH0’, ‘L’, ‘ER0’, ’ ', ‘P’, ‘EH1’, ‘T’, ‘S’, ’ ', ‘,’, ’ ', ‘F’, ‘AO1’, ‘R’, ’ ', ‘IH0’, ‘G’, ‘Z’, ‘AE1’, ‘M’, ‘P’, ‘AH0’, ‘L’, ’ ', ‘K’, ‘AE1’, ‘T’, ‘S’, ’ ', ‘AH0’, ‘N’, ‘D’, ’ ', ‘D’, ‘AA1’, ‘G’, ‘Z’]
[‘AY1’, ’ ', ‘R’, ‘IH0’, ‘F’, ‘Y’, ‘UW1’, ‘Z’, ’ ', ‘T’, ‘UW1’, ’ ', ‘K’, ‘AH0’, ‘L’, ‘EH1’, ‘K’, ‘T’, ’ ', ‘DH’, ‘AH0’, ’ ', ‘R’, ‘EH1’, ‘F’, ‘Y’, ‘UW2’, ‘Z’, ’ ', ‘ER0’, ‘AW1’, ‘N’, ‘D’, ’ ', ‘HH’, ‘IY1’, ‘R’, ’ ', ‘.’]
[‘AY1’, ‘M’, ’ ', ‘AE1’, ‘N’, ’ ', ‘AE2’, ‘K’, ‘T’, ‘IH0’, ‘V’, ‘EY1’, ‘SH’, ‘AH0’, ‘N’, ‘IH0’, ‘S’, ‘T’, ’ ', ‘.’]