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# -*- coding: utf-8 -*-
import json
import logging
import re
import torch
from dragonmapper.transcriptions import pinyin_to_ipa
from phonemizer.backend import EspeakBackend
from pypinyin import pinyin
from Preprocessing.articulatory_features import generate_feature_table
from Preprocessing.articulatory_features import get_feature_to_index_lookup
from Preprocessing.articulatory_features import get_phone_to_id
def load_json_from_path(path): # redundant to the one in utils, but necessary to avoid circular imports
with open(path, "r", encoding="utf8") as f:
obj = json.loads(f.read())
return obj
class ArticulatoryCombinedTextFrontend:
def __init__(self,
language,
use_explicit_eos=True,
use_lexical_stress=True,
silent=True,
add_silence_to_end=True,
use_word_boundaries=True,
device="cpu"):
"""
Mostly preparing ID lookups
"""
# this locks the device, so it has to happen here and not at the top
from transphone.g2p import read_g2p
self.language = language
self.use_explicit_eos = use_explicit_eos
self.use_stress = use_lexical_stress
self.add_silence_to_end = add_silence_to_end
self.use_word_boundaries = use_word_boundaries
register_to_height = {
"˥": 5,
"˦": 4,
"˧": 3,
"˨": 2,
"˩": 1
}
self.rising_perms = list()
self.falling_perms = list()
self.peaking_perms = list()
self.dipping_perms = list()
for first_tone in ["˥", "˦", "˧", "˨", "˩"]:
for second_tone in ["˥", "˦", "˧", "˨", "˩"]:
if register_to_height[first_tone] > register_to_height[second_tone]:
self.falling_perms.append(first_tone + second_tone)
else:
self.rising_perms.append(first_tone + second_tone)
for third_tone in ["˥", "˦", "˧", "˨", "˩"]:
if register_to_height[first_tone] > register_to_height[second_tone] < register_to_height[third_tone]:
self.dipping_perms.append(first_tone + second_tone + third_tone)
elif register_to_height[first_tone] < register_to_height[second_tone] > register_to_height[third_tone]:
self.peaking_perms.append(first_tone + second_tone + third_tone)
if language == "eng" or language == "en-us":
self.g2p_lang = "en-us" # English as spoken in USA
self.expand_abbreviations = english_text_expansion
self.phonemizer = "espeak"
elif language == "deu":
self.g2p_lang = "de" # German
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ell":
self.g2p_lang = "el" # Greek
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "spa":
self.g2p_lang = "es" # Spanish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "spa-lat":
self.g2p_lang = "es-419" # Spanish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "fin":
self.g2p_lang = "fi" # Finnish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "rus":
self.g2p_lang = "ru" # Russian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hun":
self.g2p_lang = "hu" # Hungarian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "nld":
self.g2p_lang = "nl" # Dutch
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "fra":
self.g2p_lang = "fr-fr" # French
self.expand_abbreviations = remove_french_spacing
self.phonemizer = "espeak"
elif language == "fr-be":
self.g2p_lang = "fr-be" # French
self.expand_abbreviations = remove_french_spacing
self.phonemizer = "espeak"
elif language == "fr-sw":
self.g2p_lang = "fr-ch" # French
self.expand_abbreviations = remove_french_spacing
self.phonemizer = "espeak"
elif language == "ita":
self.g2p_lang = "it" # Italian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "por":
self.g2p_lang = "pt" # Portuguese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "pt-br":
self.g2p_lang = "pt-br" # Portuguese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "pol":
self.g2p_lang = "pl" # Polish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "cmn":
self.g2p_lang = "cmn" # Mandarin
self.expand_abbreviations = convert_kanji_to_pinyin_mandarin
self.phonemizer = "dragonmapper"
elif language == "vie":
self.g2p_lang = "vi" # Northern Vietnamese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "vi-ctr":
self.g2p_lang = "vi-vn-x-central" # Central Vietnamese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "vi-so":
self.g2p_lang = "vi-vn-x-south" # Southern Vietnamese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ukr":
self.g2p_lang = "uk" # Ukrainian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "pes":
self.g2p_lang = "fa" # Western Farsi
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "afr":
self.g2p_lang = "af" # Afrikaans
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "aln":
self.g2p_lang = "sq" # Albanian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "amh":
self.g2p_lang = "am" # Amharic
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "arb":
self.g2p_lang = "ar" # Arabic
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "arg":
self.g2p_lang = "an" # Aragonese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hye":
self.g2p_lang = "hy" # East Armenian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hyw":
self.g2p_lang = "hyw" # West Armenian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "azj":
self.g2p_lang = "az" # Azerbaijani
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "bak":
self.g2p_lang = "ba" # Bashkir
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "eus":
self.g2p_lang = "eu" # Basque
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "bel":
self.g2p_lang = "be" # Belarusian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ben":
self.g2p_lang = "bn" # Bengali
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "bpy":
self.g2p_lang = "bpy" # Bishnupriya Manipuri
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "bos":
self.g2p_lang = "bs" # Bosnian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "bul":
self.g2p_lang = "bg" # Bulgarian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mya":
self.g2p_lang = "my" # Burmese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "chr":
self.g2p_lang = "chr" # Cherokee
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "yue":
self.g2p_lang = "yue" # Chinese Cantonese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hak":
self.g2p_lang = "hak" # Chinese Hakka
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "haw":
self.g2p_lang = "haw" # Hawaiian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hrv":
self.g2p_lang = "hr" # Croatian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ces":
self.g2p_lang = "cs" # Czech
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "dan":
self.g2p_lang = "da" # Danish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ekk":
self.g2p_lang = "et" # Estonian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "gle":
self.g2p_lang = "ga" # Gaelic Irish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "gla":
self.g2p_lang = "gd" # Gaelic Scottish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "en-sc":
self.g2p_lang = "en-gb-scotland"
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "kat":
self.g2p_lang = "ka" # Georgian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "kal":
self.g2p_lang = "kl" # Greenlandic
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "guj":
self.g2p_lang = "gu" # Gujarati
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "heb":
self.g2p_lang = "he" # Hebrew
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "hin":
self.g2p_lang = "hi" # Hindi
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "isl":
self.g2p_lang = "is" # Icelandic
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ind":
self.g2p_lang = "id" # Indonesian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "jpn":
import pykakasi
self.kakasi = pykakasi.Kakasi() # this is not a satisfactory solution, but it is the best one I could come up with so far.
self.expand_abbreviations = lambda x: " ".join([chunk["hepburn"] for chunk in self.kakasi.convert(x)])
self.g2p_lang = language
self.phonemizer = "transphone"
self.transphone = read_g2p(device=device)
elif language == "kan":
self.g2p_lang = "kn" # Kannada
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "knn":
self.g2p_lang = "kok" # Konkani
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "kor":
self.g2p_lang = "ko" # Korean
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ckb":
self.g2p_lang = "ku" # Kurdish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "kaz":
self.g2p_lang = "kk" # Kazakh
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "kir":
self.g2p_lang = "ky" # Kyrgyz
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "lat":
self.g2p_lang = "la" # Latin
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ltz":
self.g2p_lang = "lb" # Luxembourgish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "lvs":
self.g2p_lang = "lv" # Latvian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "lit":
self.g2p_lang = "lt" # Lithuanian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mri":
self.g2p_lang = "mi" # Māori
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mkd":
self.g2p_lang = "mk" # Macedonian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "zlm":
self.g2p_lang = "ms" # Malay
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mal":
self.g2p_lang = "ml" # Malayalam
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mlt":
self.g2p_lang = "mt" # Maltese
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "mar":
self.g2p_lang = "mr" # Marathi
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "nci":
self.g2p_lang = "nci" # Nahuatl
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "npi":
self.g2p_lang = "ne" # Nepali
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "nob":
self.g2p_lang = "nb" # Norwegian Bokmål
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "nog":
self.g2p_lang = "nog" # Nogai
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ory":
self.g2p_lang = "or" # Oriya
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "gaz":
self.g2p_lang = "om" # Oromo
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "pap":
self.g2p_lang = "pap" # Papiamento
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "pan":
self.g2p_lang = "pa" # Punjabi
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "ron":
self.g2p_lang = "ro" # Romanian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "lav":
self.g2p_lang = "ru-lv" # Russian Latvia
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "srp":
self.g2p_lang = "sr" # Serbian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tsn":
self.g2p_lang = "tn" # Setswana
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "snd":
self.g2p_lang = "sd" # Sindhi
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "slk":
self.g2p_lang = "sk" # Slovak
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "slv":
self.g2p_lang = "sl" # Slovenian
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "smj":
self.g2p_lang = "smj" # Lule Saami
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "swh":
self.g2p_lang = "sw" # Swahili
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "swe":
self.g2p_lang = "sv" # Swedish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tam":
self.g2p_lang = "ta" # Tamil
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tha":
self.g2p_lang = "th" # Thai
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tuk":
self.g2p_lang = "tk" # Turkmen
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tat":
self.g2p_lang = "tt" # Tatar
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tel":
self.g2p_lang = "te" # Telugu
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "tur":
self.g2p_lang = "tr" # Turkish
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "uig":
self.g2p_lang = "ug" # Uyghur
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "urd":
self.g2p_lang = "ur" # Urdu
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "uzn":
self.g2p_lang = "uz" # Uzbek
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
elif language == "cym":
self.g2p_lang = "cy" # Welsh
self.expand_abbreviations = lambda x: x
self.phonemizer = "espeak"
else:
# blanket solution for the rest
print("Using Transphone. A specialized phonemizer might work better.")
self.g2p_lang = language
self.phonemizer = "transphone"
self.expand_abbreviations = lambda x: x
self.transphone = read_g2p(device=device)
# remember to also update get_language_id() below when adding something here, as well as the get_example_sentence function
if self.phonemizer == "espeak":
try:
self.phonemizer_backend = EspeakBackend(language=self.g2p_lang,
punctuation_marks=';:,.!?¡¿—…()"«»“”~/。【】、‥،؟“”؛',
preserve_punctuation=True,
language_switch='remove-flags',
with_stress=self.use_stress,
logger=logging.getLogger(__file__))
except RuntimeError:
print("Error in loading espeak! \n"
"Maybe espeak is not installed on your system? \n"
"Falling back to transphone.")
from transphone.g2p import read_g2p
self.g2p_lang = self.language
self.phonemizer = "transphone"
self.expand_abbreviations = lambda x: x
self.transphone = read_g2p()
self.phone_to_vector = generate_feature_table()
self.phone_to_id = get_phone_to_id()
self.id_to_phone = {v: k for k, v in self.phone_to_id.items()}
self.text_vector_to_phone_cache = dict()
@staticmethod
def get_example_sentence(lang):
if lang == "eng":
return "This is a complex sentence, it even has a pause!"
elif lang == "deu":
return "Dies ist ein komplexer Satz, er hat sogar eine Pause!"
elif lang == "ell":
return "Αυτή είναι μια σύνθετη πρόταση, έχει ακόμη και παύση!"
elif lang == "spa":
return "Esta es una oración compleja, ¡incluso tiene una pausa!"
elif lang == "fin":
return "Tämä on monimutkainen lause, sillä on jopa tauko!"
elif lang == "rus":
return "Это сложное предложение, в нем даже есть пауза!"
elif lang == "hun":
return "Ez egy összetett mondat, még szünet is van benne!"
elif lang == "nld":
return "Dit is een complexe zin, er zit zelfs een pauze in!"
elif lang == "fra":
return "C'est une phrase complexe, elle a même une pause !"
elif lang == "por":
return "Esta é uma frase complexa, tem até uma pausa!"
elif lang == "pol":
return "To jest zdanie złożone, ma nawet pauzę!"
elif lang == "ita":
return "Questa è una frase complessa, ha anche una pausa!"
elif lang == "cmn":
return "这是一个复杂的句子,它甚至包含一个停顿。"
elif lang == "vie":
return "Đây là một câu phức tạp, nó thậm chí còn chứa một khoảng dừng."
else:
print(f"No example sentence specified for the language: {lang}\n "
f"Please specify an example sentence in the get_example_sentence function in Preprocessing/TextFrontend to track your progress.")
return None
def string_to_tensor(self, text, view=False, device="cpu", handle_missing=True, input_phonemes=False):
"""
Fixes unicode errors, expands some abbreviations,
turns graphemes into phonemes and then vectorizes
the sequence as articulatory features
"""
if input_phonemes:
phones = text
else:
phones = self.get_phone_string(text=text, include_eos_symbol=True, for_feature_extraction=True)
phones = phones.replace("ɚ", "ə").replace("ᵻ", "ɨ")
if view:
print("Phonemes: \n{}\n".format(phones))
phones_vector = list()
# turn into numeric vectors
stressed_flag = False
for char in phones:
# affects following phoneme -----------------
if char.strip() == '\u02C8':
# primary stress
stressed_flag = True
# affects previous phoneme -----------------
elif char.strip() == '\u02D0':
# lengthened
phones_vector[-1][get_feature_to_index_lookup()["lengthened"]] = 1
elif char.strip() == '\u02D1':
# half length
phones_vector[-1][get_feature_to_index_lookup()["half-length"]] = 1
elif char.strip() == '\u0306':
# shortened
phones_vector[-1][get_feature_to_index_lookup()["shortened"]] = 1
elif char.strip() == '̃' and phones_vector[-1][get_feature_to_index_lookup()["nasal"]] != 1:
# nasalized (vowel)
phones_vector[-1][get_feature_to_index_lookup()["nasal"]] = 2
elif char.strip() == "̧" != phones_vector[-1][get_feature_to_index_lookup()["palatal"]] != 1:
# palatalized
phones_vector[-1][get_feature_to_index_lookup()["palatal"]] = 2
elif char.strip() == "ʷ" and phones_vector[-1][get_feature_to_index_lookup()["labial-velar"]] != 1:
# labialized
phones_vector[-1][get_feature_to_index_lookup()["labial-velar"]] = 2
elif char.strip() == "ʰ" and phones_vector[-1][get_feature_to_index_lookup()["aspirated"]] != 1:
# aspirated
phones_vector[-1][get_feature_to_index_lookup()["aspirated"]] = 2
elif char.strip() == "ˠ" and phones_vector[-1][get_feature_to_index_lookup()["velar"]] != 1:
# velarized
phones_vector[-1][get_feature_to_index_lookup()["velar"]] = 2
elif char.strip() == "ˁ" and phones_vector[-1][get_feature_to_index_lookup()["pharyngal"]] != 1:
# pharyngealized
phones_vector[-1][get_feature_to_index_lookup()["pharyngal"]] = 2
elif char.strip() == "ˀ" and phones_vector[-1][get_feature_to_index_lookup()["glottal"]] != 1:
# glottalized
phones_vector[-1][get_feature_to_index_lookup()["glottal"]] = 2
elif char.strip() == "ʼ" and phones_vector[-1][get_feature_to_index_lookup()["ejective"]] != 1:
# ejective
phones_vector[-1][get_feature_to_index_lookup()["ejective"]] = 2
elif char.strip() == "̹" and phones_vector[-1][get_feature_to_index_lookup()["rounded"]] != 1:
# rounding
phones_vector[-1][get_feature_to_index_lookup()["rounded"]] = 2
elif char.strip() == "̞" and phones_vector[-1][get_feature_to_index_lookup()["open"]] != 1:
# open
phones_vector[-1][get_feature_to_index_lookup()["open"]] = 2
elif char.strip() == "̪" and phones_vector[-1][get_feature_to_index_lookup()["dental"]] != 1:
# dental
phones_vector[-1][get_feature_to_index_lookup()["dental"]] = 2
elif char.strip() == "̬" and phones_vector[-1][get_feature_to_index_lookup()["voiced"]] != 1:
# voiced
phones_vector[-1][get_feature_to_index_lookup()["voiced"]] = 2
elif char.strip() == "̝" and phones_vector[-1][get_feature_to_index_lookup()["close"]] != 1:
# closed
phones_vector[-1][get_feature_to_index_lookup()["close"]] = 2
elif char.strip() == "̰" and phones_vector[-1][get_feature_to_index_lookup()["glottal"]] != 1 and phones_vector[-1][get_feature_to_index_lookup()["epiglottal"]] != 1:
# laryngalization
phones_vector[-1][get_feature_to_index_lookup()["glottal"]] = 2
phones_vector[-1][get_feature_to_index_lookup()["epiglottal"]] = 2
elif char.strip() == "̈" and phones_vector[-1][get_feature_to_index_lookup()["central"]] != 1:
# centralization
phones_vector[-1][get_feature_to_index_lookup()["central"]] = 2
elif char.strip() == "̜" and phones_vector[-1][get_feature_to_index_lookup()["unrounded"]] != 1:
# unrounded
phones_vector[-1][get_feature_to_index_lookup()["unrounded"]] = 2
elif char.strip() == "̥" and phones_vector[-1][get_feature_to_index_lookup()["unvoiced"]] != 1:
# voiceless
phones_vector[-1][get_feature_to_index_lookup()["unvoiced"]] = 2
elif char.strip() == "˥":
# very high tone
phones_vector[-1][get_feature_to_index_lookup()["very-high-tone"]] = 1
elif char.strip() == "˦":
# high tone
phones_vector[-1][get_feature_to_index_lookup()["high-tone"]] = 1
elif char.strip() == "˧":
# mid tone
phones_vector[-1][get_feature_to_index_lookup()["mid-tone"]] = 1
elif char.strip() == "˨":
# low tone
phones_vector[-1][get_feature_to_index_lookup()["low-tone"]] = 1
elif char.strip() == "˩":
# very low tone
phones_vector[-1][get_feature_to_index_lookup()["very-low-tone"]] = 1
elif char.strip() == "⭧":
# rising tone
phones_vector[-1][get_feature_to_index_lookup()["rising-tone"]] = 1
elif char.strip() == "⭨":
# falling tone
phones_vector[-1][get_feature_to_index_lookup()["falling-tone"]] = 1
elif char.strip() == "⮁":
# peaking tone
phones_vector[-1][get_feature_to_index_lookup()["peaking-tone"]] = 1
elif char.strip() == "⮃":
# dipping tone
phones_vector[-1][get_feature_to_index_lookup()["dipping-tone"]] = 1
else:
if handle_missing:
try:
phones_vector.append(self.phone_to_vector[char].copy())
except KeyError:
print("unknown phoneme: {}".format(char))
else:
phones_vector.append(self.phone_to_vector[char].copy()) # leave error handling to elsewhere
# the following lines try to emulate whispering by removing all voiced features
# phones_vector[-1][get_feature_to_index_lookup()["voiced"]] = 0
# phones_vector[-1][get_feature_to_index_lookup()["unvoiced"]] = 1
# the following lines explore what would happen, if the system is told to produce sounds a human cannot
# for dim, _ in enumerate(phones_vector[-1]):
# phones_vector[-1][dim] = 1
if stressed_flag:
stressed_flag = False
phones_vector[-1][get_feature_to_index_lookup()["stressed"]] = 1
return torch.Tensor(phones_vector, device=device)
def get_phone_string(self, text, include_eos_symbol=True, for_feature_extraction=False, for_plot_labels=False):
if text == "":
return ""
# expand abbreviations
utt = self.expand_abbreviations(text)
# convert the graphemes to phonemes here
if self.phonemizer == "espeak":
try:
phones = self.phonemizer_backend.phonemize([utt], strip=True)[0] # To use a different phonemizer, this is the only line that needs to be exchanged
except:
print(f"There was an error with espeak. \nFalling back to transphone.\nSentence: {utt} \nLanguage {self.g2p_lang}")
from transphone.g2p import read_g2p
self.g2p_lang = self.language
self.phonemizer = "transphone"
self.expand_abbreviations = lambda x: x
self.transphone = read_g2p()
return self.get_phone_string(text, include_eos_symbol, for_feature_extraction, for_plot_labels)
elif self.phonemizer == "transphone":
replacements = [
# punctuation in languages with non-latin script
("。", "~"),
(",", "~"),
("【", '~'),
("】", '~'),
("、", "~"),
("‥", "~"),
("؟", "~"),
("،", "~"),
("“", '~'),
("”", '~'),
("؛", "~"),
("《", '~'),
("》", '~'),
("?", "~"),
("!", "~"),
(" :", "~"),
(" ;", "~"),
("-", "~"),
("·", " "),
("`", ""),
# symbols that indicate a pause or silence
('"', "~"),
(" - ", "~ "),
("- ", "~ "),
("-", ""),
("…", "~"),
(":", "~"),
(";", "~"),
(",", "~") # make sure this remains the final one when adding new ones
]
for replacement in replacements:
utt = utt.replace(replacement[0], replacement[1])
utt = re.sub("~+", "~", utt)
utt = re.sub(r"\s+", " ", utt)
utt = re.sub(r"\.+", ".", utt)
chunk_list = list()
for chunk in utt.split("~"):
# unfortunately the transphone tokenizer is not suited for any languages besides English it seems
# this is not much better, but maybe a little.
word_list = list()
for word_by_whitespace in chunk.split():
word_list.append(self.transphone.inference(word_by_whitespace, self.g2p_lang))
chunk_list.append(" ".join(["".join(word) for word in word_list]))
phones = "~ ".join(chunk_list)
elif self.phonemizer == "dragonmapper":
phones = pinyin_to_ipa(utt)
# Unfortunately tonal languages don't agree on the tone, most tonal
# languages use different tones denoted by different numbering
# systems. At this point in the script, it is attempted to unify
# them all to the tones in the IPA standard.
if self.g2p_lang == "vi":
phones = phones.replace('1', "˧")
phones = phones.replace('2', "˨˩")
phones = phones.replace('ɜ', "˧˥") # I'm fairly certain that this is a bug in espeak and ɜ is meant to be 3
phones = phones.replace('3', "˧˥") # I'm fairly certain that this is a bug in espeak and ɜ is meant to be 3
phones = phones.replace('4', "˦˧˥")
phones = phones.replace('5', "˧˩˧")
phones = phones.replace('6', "˧˩˨ʔ") # very weird tone, because the tone introduces another phoneme
phones = phones.replace('7', "˧")
elif self.g2p_lang == "yue":
phones = phones.replace('1', "˥")
phones = phones.replace('2', "˧˥")
phones = phones.replace('3', "˧")
phones = phones.replace('4', "˧˩")
phones = phones.replace('5', "˩˧")
phones = phones.replace('6', "˨")
# more of this handling for more tonal languages can be added here, simply make an elif statement and check for the language.
return self.postprocess_phoneme_string(phones, for_feature_extraction, include_eos_symbol, for_plot_labels)
def postprocess_phoneme_string(self, phoneme_string, for_feature_extraction, include_eos_symbol, for_plot_labels):
"""
Takes as input a phoneme string and processes it to work best with the way we represent phonemes as featurevectors
"""
replacements = [
# punctuation in languages with non-latin script
("。", "."),
(",", ","),
("【", '"'),
("】", '"'),
("、", ","),
("‥", "…"),
("؟", "?"),
("،", ","),
("“", '"'),
("”", '"'),
("؛", ","),
("《", '"'),
("》", '"'),
("?", "?"),
("!", "!"),
(" :", ":"),
(" ;", ";"),
("-", "-"),
("·", " "),
# latin script punctuation
("/", " "),
("—", ""),
("(", "~"),
(")", "~"),
("...", "…"),
("\n", ", "),
("\t", " "),
("¡", ""),
("¿", ""),
("«", '"'),
("»", '"'),
# unifying some phoneme representations
("N", "ŋ"), # somehow transphone doesn't transform this to IPA
("ɫ", "l"), # alveolopalatal
("ɚ", "ə"),
("g", "ɡ"),
("ε", "e"),
("ʦ", "ts"),
("ˤ", "ˁ"),
('ᵻ', 'ɨ'),
("ɧ", "ç"), # velopalatal
("ɥ", "j"), # labiopalatal
("ɬ", "s"), # lateral
("ɮ", "z"), # lateral
('ɺ', 'ɾ'), # lateral
('ʲ', 'j'), # decomposed palatalization
('\u02CC', ""), # secondary stress
('\u030B', "˥"),
('\u0301', "˦"),
('\u0304', "˧"),
('\u0300', "˨"),
('\u030F', "˩"),
('\u0302', "⭨"),
('\u030C', "⭧"),
("꜖", "˩"),
("꜕", "˨"),
("꜔", "˧"),
("꜓", "˦"),
("꜒", "˥"),
# symbols that indicate a pause or silence
('"', "~"),
(" - ", "~ "),
("- ", "~ "),
("-", ""),
("…", "."),
(":", "~"),
(";", "~"),
(",", "~") # make sure this remains the final one when adding new ones
]
unsupported_ipa_characters = {'̙', '̯', '̤', '̩', '̠', '̟', 'ꜜ', '̽', '|', '•', '↘',
'‖', '‿', 'ᷝ', 'ᷠ', '̚', '↗', 'ꜛ', '̻', '̘', '͡', '̺'}
# https://en.wikipedia.org/wiki/IPA_number
for char in unsupported_ipa_characters:
replacements.append((char, ""))
if not for_feature_extraction:
# in case we want to plot etc., we only need the segmental units, so we remove everything else.
replacements = replacements + [
('\u02C8', ""), # primary stress
('\u02D0', ""), # lengthened
('\u02D1', ""), # half-length
('\u0306', ""), # shortened
("˥", ""), # very high tone
("˦", ""), # high tone
("˧", ""), # mid tone
("˨", ""), # low tone
("˩", ""), # very low tone
('\u030C', ""), # rising tone
('\u0302', ""), # falling tone
('⭧', ""), # rising
('⭨', ""), # falling
('⮃', ""), # dipping
('⮁', ""), # peaking
('̃', ""), # nasalizing
("̧", ""), # palatalized
("ʷ", ""), # labialized
("ʰ", ""), # aspirated
("ˠ", ""), # velarized
("ˁ", ""), # pharyngealized
("ˀ", ""), # glottalized
("ʼ", ""), # ejective
("̹", ""), # rounding
("̞", ""), # open
("̪", ""), # dental
("̬", ""), # voiced
("̝", ""), # closed
("̰", ""), # laryngalization
("̈", ""), # centralization
("̜", ""), # unrounded
("̥", ""), # voiceless
]
for replacement in replacements:
phoneme_string = phoneme_string.replace(replacement[0], replacement[1])
phones = re.sub("~+", "~", phoneme_string)
phones = re.sub(r"\s+", " ", phones)
phones = re.sub(r"\.+", ".", phones)
phones = phones.lstrip("~").rstrip("~")
# peaking tones
for peaking_perm in self.peaking_perms:
phones = phones.replace(peaking_perm, "⮁".join(peaking_perm))
# dipping tones
for dipping_perm in self.dipping_perms:
phones = phones.replace(dipping_perm, "⮃".join(dipping_perm))
# rising tones
for rising_perm in self.rising_perms:
phones = phones.replace(rising_perm, "⭧".join(rising_perm))
# falling tones
for falling_perm in self.falling_perms:
phones = phones.replace(falling_perm, "⭨".join(falling_perm))
if self.add_silence_to_end:
phones += "~" # adding a silence in the end during inference produces more natural sounding prosody
if include_eos_symbol:
phones += "#"
if not self.use_word_boundaries:
phones = phones.replace(" ", "")
if for_plot_labels:
phones = phones.replace(" ", "|")
phones = "~" + phones
phones = re.sub("~+", "~", phones)
return phones
def text_vectors_to_id_sequence(self, text_vector):
tokens = list()
for vector in text_vector:
if vector[get_feature_to_index_lookup()["word-boundary"]] == 0:
# we don't include word boundaries when performing alignment, since they are not always present in audio.
features = vector.cpu().numpy().tolist()
immutable_vector = tuple(features)
if immutable_vector in self.text_vector_to_phone_cache:
tokens.append(self.phone_to_id[self.text_vector_to_phone_cache[immutable_vector]])
continue
features = features[13:]
# the first 12 dimensions are for modifiers, so we ignore those when trying to find the phoneme in the ID lookup
for index in range(len(features)):
if features[index] == 2:
# we remove all features that stem from a modifier, so we can map back to the unmodified sound
features[index] = 0
for phone in self.phone_to_vector:
if features == self.phone_to_vector[phone][13:]:
tokens.append(self.phone_to_id[phone])
self.text_vector_to_phone_cache[immutable_vector] = phone
# this is terribly inefficient, but it's fine, since we're building a cache over time that makes this instant
break
return tokens
def english_text_expansion(text):
"""
Apply as small part of the tacotron style text cleaning pipeline, suitable for e.g. LJSpeech.
See https://github.com/keithito/tacotron/
Careful: Only apply to english datasets. Different languages need different cleaners.
"""
_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in
[('Mrs.', 'misess'), ('Mr.', 'mister'), ('Dr.', 'doctor'), ('St.', 'saint'), ('Co.', 'company'), ('Jr.', 'junior'), ('Maj.', 'major'),
('Gen.', 'general'), ('Drs.', 'doctors'), ('Rev.', 'reverend'), ('Lt.', 'lieutenant'), ('Hon.', 'honorable'), ('Sgt.', 'sergeant'),
('Capt.', 'captain'), ('Esq.', 'esquire'), ('Ltd.', 'limited'), ('Col.', 'colonel'), ('Ft.', 'fort')]]
for regex, replacement in _abbreviations:
text = re.sub(regex, replacement, text)
return text
def remove_french_spacing(text):
text = text.replace(" »", '"').replace("« ", '"')
for punc in ["!", ";", ":", ".", ",", "?", "-"]:
text = text.replace(f" {punc}", punc)
return text
def convert_kanji_to_pinyin_mandarin(text):
return " ".join([x[0] for x in pinyin(text)])
def get_language_id(language):
try:
iso_codes_to_ids = load_json_from_path("Preprocessing/multilinguality/iso_lookup.json")[-1]
except FileNotFoundError:
try:
iso_codes_to_ids = load_json_from_path("multilinguality/iso_lookup.json")[-1]
except FileNotFoundError:
iso_codes_to_ids = load_json_from_path("iso_lookup.json")[-1]
if language not in iso_codes_to_ids:
print("Please specify the language as ISO 639-3 code (https://en.wikipedia.org/wiki/List_of_ISO_639-3_codes)")
return None
return torch.LongTensor([iso_codes_to_ids[language]])
if __name__ == '__main__':
print("\n\nEnglish Test")
tf = ArticulatoryCombinedTextFrontend(language="eng")
tf.string_to_tensor("This is a complex sentence, it even has a pause! But can it do this? Nice.", view=True)
print("\n\nChinese Test")
tf = ArticulatoryCombinedTextFrontend(language="cmn")
tf.string_to_tensor("这是一个复杂的句子,它甚至包含一个停顿。", view=True)
tf.string_to_tensor("李绅 《悯农》 锄禾日当午, 汗滴禾下土。 谁知盘中餐, 粒粒皆辛苦。", view=True)
tf.string_to_tensor("巴 拔 把 爸 吧", view=True)
print("\n\nVietnamese Test")
tf = ArticulatoryCombinedTextFrontend(language="vie")
tf.string_to_tensor("Xin chào thế giới, quả là một ngày tốt lành để học nói tiếng Việt!", view=True)
tf.string_to_tensor("ba bà bá bạ bả bã", view=True)
print("\n\nJapanese Test")
tf = ArticulatoryCombinedTextFrontend(language="jpn")
tf.string_to_tensor("医師会がなくても、近隣の病院なら紹介してくれると思います。", view=True)
print(tf.get_phone_string("医師会がなくても、近隣の病院なら紹介してくれると思います。"))
print("\n\nZero-Shot Test")
tf = ArticulatoryCombinedTextFrontend(language="acr")
tf.string_to_tensor("I don't know this language, but this is just a dummy text anyway.", view=True)
print(tf.get_phone_string("I don't know this language, but this is just a dummy text anyway."))
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