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childes.py
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childes.py
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# CHILDES XML Corpus Reader
# Copyright (C) 2001-2022 NLTK Project
# Author: Tomonori Nagano <tnagano@gc.cuny.edu>
# Alexis Dimitriadis <A.Dimitriadis@uu.nl>
# URL: <https://www.nltk.org/>
# For license information, see LICENSE.TXT
"""
Corpus reader for the XML version of the CHILDES corpus.
"""
__docformat__ = "epytext en"
import re
from collections import defaultdict
from nltk.corpus.reader.util import concat
from nltk.corpus.reader.xmldocs import ElementTree, XMLCorpusReader
from nltk.util import LazyConcatenation, LazyMap, flatten
# to resolve the namespace issue
NS = "http://www.talkbank.org/ns/talkbank"
class CHILDESCorpusReader(XMLCorpusReader):
"""
Corpus reader for the XML version of the CHILDES corpus.
The CHILDES corpus is available at ``https://childes.talkbank.org/``. The XML
version of CHILDES is located at ``https://childes.talkbank.org/data-xml/``.
Copy the needed parts of the CHILDES XML corpus into the NLTK data directory
(``nltk_data/corpora/CHILDES/``).
For access to the file text use the usual nltk functions,
``words()``, ``sents()``, ``tagged_words()`` and ``tagged_sents()``.
"""
def __init__(self, root, fileids, lazy=True):
XMLCorpusReader.__init__(self, root, fileids)
self._lazy = lazy
def words(
self,
fileids=None,
speaker="ALL",
stem=False,
relation=False,
strip_space=True,
replace=False,
):
"""
:return: the given file(s) as a list of words
:rtype: list(str)
:param speaker: If specified, select specific speaker(s) defined
in the corpus. Default is 'ALL' (all participants). Common choices
are 'CHI' (the child), 'MOT' (mother), ['CHI','MOT'] (exclude
researchers)
:param stem: If true, then use word stems instead of word strings.
:param relation: If true, then return tuples of (stem, index,
dependent_index)
:param strip_space: If true, then strip trailing spaces from word
tokens. Otherwise, leave the spaces on the tokens.
:param replace: If true, then use the replaced (intended) word instead
of the original word (e.g., 'wat' will be replaced with 'watch')
"""
sent = None
pos = False
if not self._lazy:
return [
self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
for fileid in self.abspaths(fileids)
]
get_words = lambda fileid: self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
return LazyConcatenation(LazyMap(get_words, self.abspaths(fileids)))
def tagged_words(
self,
fileids=None,
speaker="ALL",
stem=False,
relation=False,
strip_space=True,
replace=False,
):
"""
:return: the given file(s) as a list of tagged
words and punctuation symbols, encoded as tuples
``(word,tag)``.
:rtype: list(tuple(str,str))
:param speaker: If specified, select specific speaker(s) defined
in the corpus. Default is 'ALL' (all participants). Common choices
are 'CHI' (the child), 'MOT' (mother), ['CHI','MOT'] (exclude
researchers)
:param stem: If true, then use word stems instead of word strings.
:param relation: If true, then return tuples of (stem, index,
dependent_index)
:param strip_space: If true, then strip trailing spaces from word
tokens. Otherwise, leave the spaces on the tokens.
:param replace: If true, then use the replaced (intended) word instead
of the original word (e.g., 'wat' will be replaced with 'watch')
"""
sent = None
pos = True
if not self._lazy:
return [
self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
for fileid in self.abspaths(fileids)
]
get_words = lambda fileid: self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
return LazyConcatenation(LazyMap(get_words, self.abspaths(fileids)))
def sents(
self,
fileids=None,
speaker="ALL",
stem=False,
relation=None,
strip_space=True,
replace=False,
):
"""
:return: the given file(s) as a list of sentences or utterances, each
encoded as a list of word strings.
:rtype: list(list(str))
:param speaker: If specified, select specific speaker(s) defined
in the corpus. Default is 'ALL' (all participants). Common choices
are 'CHI' (the child), 'MOT' (mother), ['CHI','MOT'] (exclude
researchers)
:param stem: If true, then use word stems instead of word strings.
:param relation: If true, then return tuples of ``(str,pos,relation_list)``.
If there is manually-annotated relation info, it will return
tuples of ``(str,pos,test_relation_list,str,pos,gold_relation_list)``
:param strip_space: If true, then strip trailing spaces from word
tokens. Otherwise, leave the spaces on the tokens.
:param replace: If true, then use the replaced (intended) word instead
of the original word (e.g., 'wat' will be replaced with 'watch')
"""
sent = True
pos = False
if not self._lazy:
return [
self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
for fileid in self.abspaths(fileids)
]
get_words = lambda fileid: self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
return LazyConcatenation(LazyMap(get_words, self.abspaths(fileids)))
def tagged_sents(
self,
fileids=None,
speaker="ALL",
stem=False,
relation=None,
strip_space=True,
replace=False,
):
"""
:return: the given file(s) as a list of
sentences, each encoded as a list of ``(word,tag)`` tuples.
:rtype: list(list(tuple(str,str)))
:param speaker: If specified, select specific speaker(s) defined
in the corpus. Default is 'ALL' (all participants). Common choices
are 'CHI' (the child), 'MOT' (mother), ['CHI','MOT'] (exclude
researchers)
:param stem: If true, then use word stems instead of word strings.
:param relation: If true, then return tuples of ``(str,pos,relation_list)``.
If there is manually-annotated relation info, it will return
tuples of ``(str,pos,test_relation_list,str,pos,gold_relation_list)``
:param strip_space: If true, then strip trailing spaces from word
tokens. Otherwise, leave the spaces on the tokens.
:param replace: If true, then use the replaced (intended) word instead
of the original word (e.g., 'wat' will be replaced with 'watch')
"""
sent = True
pos = True
if not self._lazy:
return [
self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
for fileid in self.abspaths(fileids)
]
get_words = lambda fileid: self._get_words(
fileid, speaker, sent, stem, relation, pos, strip_space, replace
)
return LazyConcatenation(LazyMap(get_words, self.abspaths(fileids)))
def corpus(self, fileids=None):
"""
:return: the given file(s) as a dict of ``(corpus_property_key, value)``
:rtype: list(dict)
"""
if not self._lazy:
return [self._get_corpus(fileid) for fileid in self.abspaths(fileids)]
return LazyMap(self._get_corpus, self.abspaths(fileids))
def _get_corpus(self, fileid):
results = dict()
xmldoc = ElementTree.parse(fileid).getroot()
for key, value in xmldoc.items():
results[key] = value
return results
def participants(self, fileids=None):
"""
:return: the given file(s) as a dict of
``(participant_property_key, value)``
:rtype: list(dict)
"""
if not self._lazy:
return [self._get_participants(fileid) for fileid in self.abspaths(fileids)]
return LazyMap(self._get_participants, self.abspaths(fileids))
def _get_participants(self, fileid):
# multidimensional dicts
def dictOfDicts():
return defaultdict(dictOfDicts)
xmldoc = ElementTree.parse(fileid).getroot()
# getting participants' data
pat = dictOfDicts()
for participant in xmldoc.findall(
f".//{{{NS}}}Participants/{{{NS}}}participant"
):
for (key, value) in participant.items():
pat[participant.get("id")][key] = value
return pat
def age(self, fileids=None, speaker="CHI", month=False):
"""
:return: the given file(s) as string or int
:rtype: list or int
:param month: If true, return months instead of year-month-date
"""
if not self._lazy:
return [
self._get_age(fileid, speaker, month)
for fileid in self.abspaths(fileids)
]
get_age = lambda fileid: self._get_age(fileid, speaker, month)
return LazyMap(get_age, self.abspaths(fileids))
def _get_age(self, fileid, speaker, month):
xmldoc = ElementTree.parse(fileid).getroot()
for pat in xmldoc.findall(f".//{{{NS}}}Participants/{{{NS}}}participant"):
try:
if pat.get("id") == speaker:
age = pat.get("age")
if month:
age = self.convert_age(age)
return age
# some files don't have age data
except (TypeError, AttributeError) as e:
return None
def convert_age(self, age_year):
"Caclculate age in months from a string in CHILDES format"
m = re.match(r"P(\d+)Y(\d+)M?(\d?\d?)D?", age_year)
age_month = int(m.group(1)) * 12 + int(m.group(2))
try:
if int(m.group(3)) > 15:
age_month += 1
# some corpora don't have age information?
except ValueError as e:
pass
return age_month
def MLU(self, fileids=None, speaker="CHI"):
"""
:return: the given file(s) as a floating number
:rtype: list(float)
"""
if not self._lazy:
return [
self._getMLU(fileid, speaker=speaker)
for fileid in self.abspaths(fileids)
]
get_MLU = lambda fileid: self._getMLU(fileid, speaker=speaker)
return LazyMap(get_MLU, self.abspaths(fileids))
def _getMLU(self, fileid, speaker):
sents = self._get_words(
fileid,
speaker=speaker,
sent=True,
stem=True,
relation=False,
pos=True,
strip_space=True,
replace=True,
)
results = []
lastSent = []
numFillers = 0
sentDiscount = 0
for sent in sents:
posList = [pos for (word, pos) in sent]
# if any part of the sentence is intelligible
if any(pos == "unk" for pos in posList):
continue
# if the sentence is null
elif sent == []:
continue
# if the sentence is the same as the last sent
elif sent == lastSent:
continue
else:
results.append([word for (word, pos) in sent])
# count number of fillers
if len({"co", None}.intersection(posList)) > 0:
numFillers += posList.count("co")
numFillers += posList.count(None)
sentDiscount += 1
lastSent = sent
try:
thisWordList = flatten(results)
# count number of morphemes
# (e.g., 'read' = 1 morpheme but 'read-PAST' is 2 morphemes)
numWords = (
len(flatten([word.split("-") for word in thisWordList])) - numFillers
)
numSents = len(results) - sentDiscount
mlu = numWords / numSents
except ZeroDivisionError:
mlu = 0
# return {'mlu':mlu,'wordNum':numWords,'sentNum':numSents}
return mlu
def _get_words(
self, fileid, speaker, sent, stem, relation, pos, strip_space, replace
):
if (
isinstance(speaker, str) and speaker != "ALL"
): # ensure we have a list of speakers
speaker = [speaker]
xmldoc = ElementTree.parse(fileid).getroot()
# processing each xml doc
results = []
for xmlsent in xmldoc.findall(".//{%s}u" % NS):
sents = []
# select speakers
if speaker == "ALL" or xmlsent.get("who") in speaker:
for xmlword in xmlsent.findall(".//{%s}w" % NS):
infl = None
suffixStem = None
suffixTag = None
# getting replaced words
if replace and xmlsent.find(f".//{{{NS}}}w/{{{NS}}}replacement"):
xmlword = xmlsent.find(
f".//{{{NS}}}w/{{{NS}}}replacement/{{{NS}}}w"
)
elif replace and xmlsent.find(f".//{{{NS}}}w/{{{NS}}}wk"):
xmlword = xmlsent.find(f".//{{{NS}}}w/{{{NS}}}wk")
# get text
if xmlword.text:
word = xmlword.text
else:
word = ""
# strip tailing space
if strip_space:
word = word.strip()
# stem
if relation or stem:
try:
xmlstem = xmlword.find(".//{%s}stem" % NS)
word = xmlstem.text
except AttributeError as e:
pass
# if there is an inflection
try:
xmlinfl = xmlword.find(
f".//{{{NS}}}mor/{{{NS}}}mw/{{{NS}}}mk"
)
word += "-" + xmlinfl.text
except:
pass
# if there is a suffix
try:
xmlsuffix = xmlword.find(
".//{%s}mor/{%s}mor-post/{%s}mw/{%s}stem"
% (NS, NS, NS, NS)
)
suffixStem = xmlsuffix.text
except AttributeError:
suffixStem = ""
if suffixStem:
word += "~" + suffixStem
# pos
if relation or pos:
try:
xmlpos = xmlword.findall(".//{%s}c" % NS)
xmlpos2 = xmlword.findall(".//{%s}s" % NS)
if xmlpos2 != []:
tag = xmlpos[0].text + ":" + xmlpos2[0].text
else:
tag = xmlpos[0].text
except (AttributeError, IndexError) as e:
tag = ""
try:
xmlsuffixpos = xmlword.findall(
".//{%s}mor/{%s}mor-post/{%s}mw/{%s}pos/{%s}c"
% (NS, NS, NS, NS, NS)
)
xmlsuffixpos2 = xmlword.findall(
".//{%s}mor/{%s}mor-post/{%s}mw/{%s}pos/{%s}s"
% (NS, NS, NS, NS, NS)
)
if xmlsuffixpos2:
suffixTag = (
xmlsuffixpos[0].text + ":" + xmlsuffixpos2[0].text
)
else:
suffixTag = xmlsuffixpos[0].text
except:
pass
if suffixTag:
tag += "~" + suffixTag
word = (word, tag)
# relational
# the gold standard is stored in
# <mor></mor><mor type="trn"><gra type="grt">
if relation == True:
for xmlstem_rel in xmlword.findall(
f".//{{{NS}}}mor/{{{NS}}}gra"
):
if not xmlstem_rel.get("type") == "grt":
word = (
word[0],
word[1],
xmlstem_rel.get("index")
+ "|"
+ xmlstem_rel.get("head")
+ "|"
+ xmlstem_rel.get("relation"),
)
else:
word = (
word[0],
word[1],
word[2],
word[0],
word[1],
xmlstem_rel.get("index")
+ "|"
+ xmlstem_rel.get("head")
+ "|"
+ xmlstem_rel.get("relation"),
)
try:
for xmlpost_rel in xmlword.findall(
f".//{{{NS}}}mor/{{{NS}}}mor-post/{{{NS}}}gra"
):
if not xmlpost_rel.get("type") == "grt":
suffixStem = (
suffixStem[0],
suffixStem[1],
xmlpost_rel.get("index")
+ "|"
+ xmlpost_rel.get("head")
+ "|"
+ xmlpost_rel.get("relation"),
)
else:
suffixStem = (
suffixStem[0],
suffixStem[1],
suffixStem[2],
suffixStem[0],
suffixStem[1],
xmlpost_rel.get("index")
+ "|"
+ xmlpost_rel.get("head")
+ "|"
+ xmlpost_rel.get("relation"),
)
except:
pass
sents.append(word)
if sent or relation:
results.append(sents)
else:
results.extend(sents)
return LazyMap(lambda x: x, results)
# Ready-to-use browser opener
"""
The base URL for viewing files on the childes website. This
shouldn't need to be changed, unless CHILDES changes the configuration
of their server or unless the user sets up their own corpus webserver.
"""
childes_url_base = r"https://childes.talkbank.org/browser/index.php?url="
def webview_file(self, fileid, urlbase=None):
"""Map a corpus file to its web version on the CHILDES website,
and open it in a web browser.
The complete URL to be used is:
childes.childes_url_base + urlbase + fileid.replace('.xml', '.cha')
If no urlbase is passed, we try to calculate it. This
requires that the childes corpus was set up to mirror the
folder hierarchy under childes.psy.cmu.edu/data-xml/, e.g.:
nltk_data/corpora/childes/Eng-USA/Cornell/??? or
nltk_data/corpora/childes/Romance/Spanish/Aguirre/???
The function first looks (as a special case) if "Eng-USA" is
on the path consisting of <corpus root>+fileid; then if
"childes", possibly followed by "data-xml", appears. If neither
one is found, we use the unmodified fileid and hope for the best.
If this is not right, specify urlbase explicitly, e.g., if the
corpus root points to the Cornell folder, urlbase='Eng-USA/Cornell'.
"""
import webbrowser
if urlbase:
path = urlbase + "/" + fileid
else:
full = self.root + "/" + fileid
full = re.sub(r"\\", "/", full)
if "/childes/" in full.lower():
# Discard /data-xml/ if present
path = re.findall(r"(?i)/childes(?:/data-xml)?/(.*)\.xml", full)[0]
elif "eng-usa" in full.lower():
path = "Eng-USA/" + re.findall(r"/(?i)Eng-USA/(.*)\.xml", full)[0]
else:
path = fileid
# Strip ".xml" and add ".cha", as necessary:
if path.endswith(".xml"):
path = path[:-4]
if not path.endswith(".cha"):
path = path + ".cha"
url = self.childes_url_base + path
webbrowser.open_new_tab(url)
print("Opening in browser:", url)
# Pausing is a good idea, but it's up to the user...
# raw_input("Hit Return to continue")
def demo(corpus_root=None):
"""
The CHILDES corpus should be manually downloaded and saved
to ``[NLTK_Data_Dir]/corpora/childes/``
"""
if not corpus_root:
from nltk.data import find
corpus_root = find("corpora/childes/data-xml/Eng-USA/")
try:
childes = CHILDESCorpusReader(corpus_root, ".*.xml")
# describe all corpus
for file in childes.fileids()[:5]:
corpus = ""
corpus_id = ""
for (key, value) in childes.corpus(file)[0].items():
if key == "Corpus":
corpus = value
if key == "Id":
corpus_id = value
print("Reading", corpus, corpus_id, " .....")
print("words:", childes.words(file)[:7], "...")
print(
"words with replaced words:",
childes.words(file, replace=True)[:7],
" ...",
)
print("words with pos tags:", childes.tagged_words(file)[:7], " ...")
print("words (only MOT):", childes.words(file, speaker="MOT")[:7], "...")
print("words (only CHI):", childes.words(file, speaker="CHI")[:7], "...")
print("stemmed words:", childes.words(file, stem=True)[:7], " ...")
print(
"words with relations and pos-tag:",
childes.words(file, relation=True)[:5],
" ...",
)
print("sentence:", childes.sents(file)[:2], " ...")
for (participant, values) in childes.participants(file)[0].items():
for (key, value) in values.items():
print("\tparticipant", participant, key, ":", value)
print("num of sent:", len(childes.sents(file)))
print("num of morphemes:", len(childes.words(file, stem=True)))
print("age:", childes.age(file))
print("age in month:", childes.age(file, month=True))
print("MLU:", childes.MLU(file))
print()
except LookupError as e:
print(
"""The CHILDES corpus, or the parts you need, should be manually
downloaded from https://childes.talkbank.org/data-xml/ and saved at
[NLTK_Data_Dir]/corpora/childes/
Alternately, you can call the demo with the path to a portion of the CHILDES corpus, e.g.:
demo('/path/to/childes/data-xml/Eng-USA/")
"""
)
# corpus_root_http = urllib2.urlopen('https://childes.talkbank.org/data-xml/Eng-USA/Bates.zip')
# corpus_root_http_bates = zipfile.ZipFile(cStringIO.StringIO(corpus_root_http.read()))
##this fails
# childes = CHILDESCorpusReader(corpus_root_http_bates,corpus_root_http_bates.namelist())
if __name__ == "__main__":
demo()