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parseTcofSync.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from xml.etree import ElementTree as ET
from sys import argv
from num2words import num2words
from unidecode import unidecode
import re
import os.path
def transformation_text(text):
bool=True
if "###" in text or len(re.findall(r"\[.+\]", text)) > 0 or \
len(re.findall(r"\p{L}+-[^\p{L}]|\p{L}+-$",text)) > 0 \
or len(re.findall("[^\p{L}]-\p{L}+|^-\p{L}+", text)) > 0:
#print text
#print "Ligne Supprime"
bool=False
else:
# 4x4
# Remove noise sound (BIP) over Name of places and person
#text = re.sub(r"¤[^ ]+|[^ ]+¤|¤", "", text.strip())
if len(re.findall(r"\dx\d",text))>0:
text=re.sub(r"x"," ",text)
if len(re.findall("\d+h\d+",text))>0:
heures=re.findall("\d+h\d+",text)
for h in heures:
split_h=h.split('h')
text_rep=split_h[0]+' heure '+split_h[1]
text=text.replace(h, text_rep)
text=re.sub(r',',' ',text)
# remove silence character : OK
#text=re.sub(r"(/.+/","remplacer par la 1er",text)
# Liaison non standard remarquable
text=re.sub(r'=','',text)
# Comment Transcriber
text=re.sub(r'\{.+\}','',text)
text=re.sub(r'\(.+\}','',text)
#print "detecter (///|/|<|>)"
# Remove undecidable variant heared like on (n') en:
text=re.sub(r"\(.+\)","",text)
#text = re.sub(r"(\+|[*]+|///|/|<|>)", "", text.strip())
#text=re.sub(r"-|_|\."," ",text.strip())
text=re.sub(r'(O.K.)','ok',text)
text = re.sub(r'(O.K)', 'ok', text)
# Replace . with ' '
text=re.sub(r'\.',' ',text)
#text=re.sub(r"{[^{]+}"," ",text.strip())
# Remove ? ! < > : OK
#<[^\p{L}]|[^\p{L}]>|#+|<\p{L}+[ ]|<\p{L}+$
text=re.sub(r":|\?|/|\!|<|>|#+","",text)
# replace silence character with <sil> : OK
#text=re.sub(r"(\+)", "<sil>", text)
text=re.sub(r"(\+)", "!SIL", text)
text=re.sub(r"(///)", "!SIL", text)
#text=re.sub(r"(///)", "<long-sil>", text)
if len(re.findall(r"/.+/", text)) > 0:
#print "AVANT***********"+text
for unchoosen_text in re.findall(r"/.+/", text):
# choose first undecideble word
unchoosen_word=unchoosen_text.split(',')
for choosen_word in unchoosen_word:
# isn't incomprehensible word
if len(re.findall(r"\*+|\d+", choosen_word))==0:
choosen_word = choosen_word.replace('/', '')
text = text.replace(unchoosen_text, choosen_word)
#print "Apres************"+text
# Remove noise sound (BIP) over Name of places and person
text=re.sub(r"(¤.+¤)",'<NOISE>',text)
# replace unkown syllable
text=re.sub(r"\*+","<SPOKEN_NOISE>",text)
# cut of recording : OK
text=re.sub(r"\$+","",text)
# remove " character: OK
text = re.sub(r"\"+", "", text)
# t 'avais
text = re.sub(r"[ ]\'", " ", text)
text = re.sub(r"\'", "\' ", text)
# convert number if exist : OK
num_list = re.findall(" \d+| \d+$", text)
if len(num_list) > 0:
#print text
#print "********************************* NUM2WORD"
for num in num_list:
num_in_word = num2words(int(num), lang='fr')
#num_in_word=normalize('NFKD', num_in_word).encode('ascii', 'ignore')
text = text.replace(str(num), " " + str(num_in_word) + " ")
#print text
# replace n succesive spaces with one space. : OK
text=re.sub(r"\s{2,}"," ",text)
text = re.sub("^ ", '', text)
# change bounding | to < and > : OK
balise=set(re.findall(r"\|\w+_?\w+\|",text))
if len(balise)>0:
#print(balise)
for b in balise:
new_balise='<'+b[1:len(b)-1]+'>'
text=text.replace(b,new_balise)
#print(text)
# c'est l'essaim ....
text=text.lower()
return bool,text
if __name__=="__main__":
# Inputs
file_trs=argv[1]
#print(file_trs)
#print file_trs
outdir=argv[2]
basename=os.path.basename(file_trs.split('.')[0])
# MetaData File
file_meta = file_trs.split('.')[0] + '.xml'
#print file_trs.split('.')[0]
# Output File needed for kaldi input
segments_file = open(outdir + '/segments', 'a')
utt2spk_file = open(outdir + '/utt2spk', 'a')
text_file = open(outdir + '/text', 'a')
wav_scp = open(outdir + '/wav.scp', 'a')
spk2gender= open(outdir + '/spk2gender', 'a')
# Read Trans File
tree_trs = ET.parse(file_trs)
trsdoc= tree_trs.getroot()
#Read MetaData Of speaker ( ID and Name)
speaker_id=[]
namespk=[]
for spk in trsdoc.iter('Speaker'):
id_spk=spk.get('id')
name_spk=unidecode(spk.get('name'))
#if isinstance(name_spk,str):
#print(type(name_spk))
#name_spk=normalize('NFKD', name_spk).encode('ascii', 'ignore')
speaker_id.append(id_spk.replace(" ",""))
namespk.append(name_spk.lower().replace(" ",""))
#Read MetaData To get Gender of Speaker (Gender and Name)
tree_meta = ET.parse(file_meta)
metadoc= tree_meta.getroot()
speaker_gender=[]
#print namespk
#print speaker_id
for loc in metadoc.iter('locuteur'):
if loc.attrib!=dict({}):
name_loc=loc.get('identifiant')
name_loc = unidecode(name_loc)
name_loc=name_loc.replace(" ","")
#print name_loc
#print name_loc
#If the gender of speaker doesn't mentioned
#print loc.findall('sexe')
if loc.findall('sexe')==[]:
speaker_gender.append([speaker_id[namespk.index(name_loc.lower())],'m'])
else:
# case 1 represent gender informat
gender_loc=loc.find('sexe').text
if gender_loc==None:
speaker_gender.append([speaker_id[namespk.index(name_loc.lower())], 'm'])
else:
#print namespk
#print namespk.index(name_loc.lower())
speaker_gender.append([speaker_id[namespk.index(name_loc.lower())],gender_loc.lower()])
#Turnlist= trsdoc.getElementsByTagName('Turn')
#Synclist= trsdoc.getElementsByTagName('Sync')
#print len(Turnlist)
#print len(Synclist)
#list_time_sync=[]Q
#for sync in Synclist:
# list_time_sync.append(float(sync.attributes['time'].value))
#a=""
#count=1
#print "#id_utt\tid_Seg\tid_Spkr\tstartTime\tendTime\tText"
text=""
Turn_count=0
count=0
has_attrib_speaker=False
# set for uniq add
Spk_that_contribute_to_meeting=set([])
start_utt=0
end_utt=0
sourceEncoding = "iso-8859-1"
targetEncoding = "utf-8"
for Element in trsdoc.iter():
if Element.tag=="Turn" and Element.get('speaker') is None:
has_attrib_speaker=False
elif Element.tag=="Turn":
# If the latest Utterance of previous Speaker is the latest one of his Turn speech
if Turn_count>0:
count = 0
#print text
### Save Files For Kaldi ###
seg_id = str(basename) + '_spk-%03d_Turn-%03d_seg-%07d' % (int(spkr.split('spk')[1]), int(Turn_count), int(count))
spkr_id=str(basename)+'_spk-%03d' % int(spkr.split('spk')[1])
bool, text = transformation_text(text)
# File wav.scp
# File utt2spk
# File text
# File speaker_gender
if bool and text!="":
segments_file.write(seg_id+" "+basename+" "+str(start_utt)+" "+str(endTime)+"\n")
start_utt=endTime
utt2spk_file.write(seg_id+" "+spkr_id+"\n")
text_file.write(seg_id+" "+text+"\n")
#for spk_tuple in speaker_gender:
# if spk_tuple[0]==spkr:
# print >> spk2gender,'%s %s' % (seg_id, spk_tuple[1])
# break
has_attrib_speaker=True
# Get id_spkr
spkr = Element.get('speaker')
#print file_trs
spkr=spkr.split()[0]
Spk_that_contribute_to_meeting.add(spkr)
#print spkr
# Get StartSegment
startTime = Element.get('startTime')
# Get EndSegment
endTime = Element.get('endTime')
# count sync for computing start and end utterance
Turn_count = Turn_count+1
elif Element.tag=="Sync" and has_attrib_speaker:
Time_start_current_sync=Element.get('time')
if count>0:
#print text
### Save Files For Kaldi ###
seg_id = str(basename) + '_spk-%03d_Turn-%03d_seg-%07d' % (int(spkr.split('spk')[1]), int(Turn_count) , int(count))
spkr_id=str(basename)+'_spk-%03d' % int(spkr.split('spk')[1])
bool, text = transformation_text(text)
end_utt=Time_start_current_sync
if bool and text!="":
segments_file.write(seg_id+" "+basename+" "+str(start_utt)+" "+str(end_utt)+"\n")
start_utt=Time_start_current_sync
utt2spk_file.write(seg_id+" "+spkr_id+"\n")
text_file.write(seg_id+" "+text+"\n")
text=Element.tail.replace('\n', '')
count=count+1
elif Element.tag=="Comment" and has_attrib_speaker and not Element.tail is None:
text=text+" "+Element.tail.replace('\n', '')
elif Element.tag=="Event" and has_attrib_speaker and not Element.tail is None :
if Element.get('type')=='noise':
if Element.get('desc')=='rire':
text=text+" |LAUGH| "+Element.tail.replace('\n', '')
else:
text=text+" |NOISE| "+Element.tail.replace('\n', '')
elif Element.get('type')=='pronounce':
text=text+" |SPOKEN_NOISE| "+Element.tail.replace('\n', '')
else:
text=text+" |NOISE| "+Element.tail.replace('\n', '')
elif Element.tag=="Who" and has_attrib_speaker and not Element.tail is None:
text=text+" "+Element.tail.replace('\n', '')
#else:
# print Element.attrib,Element.tag
# text=str(Element.tail)
# print "*********warning********"+text
# Les phrases appartenant � un tour de parole
# The last Turn, check if count >0 and add latest utterance
#print count
#print has_attrib_speaker
#print Element.tail
if count > 0 and has_attrib_speaker and not Element.tail is None:
#print text
### Save Files For Kaldi ###
seg_id = str(basename) + '_spk-%03d_Turn-%03d_seg-%07d' % (
int(spkr.split('spk')[1]), int(Turn_count), int(count))
spkr_id = str(basename) + '_spk-%03d' % int(spkr.split('spk')[1])
bool, text = transformation_text(text)
if bool and text != "":
segments_file.write(seg_id+" "+basename+" "+str(start_utt)+" "+str(endTime)+"\n")
utt2spk_file.write(seg_id+" "+spkr_id+"\n")
text_file.write(seg_id+" "+text+"\n")
for spk in speaker_gender:
if spk[0] in Spk_that_contribute_to_meeting:
spk_id = str(basename)+'_spk-%03d' % int(spk[0].split('spk')[1])
spk2gender.write(spk_id+" "+spk[1]+"\n")
wav_scp.write(basename+" sox "+os.path.dirname(file_trs) + '/' + basename + '.wav'+" -t wav -r 16000 -c 1 - |\n")
segments_file.close()
utt2spk_file.close()
text_file.close()
wav_scp.close()