def interact(self) -> None:
while True:
if self.SpeechRecognition:
with sr.Microphone() as source:
self.r.adjust_for_ambient_noise(source, duration=1)
print("Dites quelque chose !")
audio = self.r.listen(source)
sentence = ""
try:
sentence = self.r.recognize_google(audio,
language="fr-FR")
print("Google pense que vous dites ca : " + sentence)
except sr.UnknownValueError:
print("Google n'a pas pu comprendre l'audio")
except sr.RequestError as e:
print(
"Impossible de faire une requete au serveurs google. Etes vous bien connecté à internet ?"
)
else:
sentence = input('> ')
if sentence == '.':
break
response_complete = self.complete(self.response(sentence))
print(response_complete)
if self.talk:
voice = Voice(lang="fr", speed=120)
voice.say(response_complete)
def make_espeak(text, lang, max_length):
voice = Voice(lang=gtts_to_espeak[lang], speed=130,
volume=2) if lang in gtts_to_espeak else Voice(lang="en",
speed=130)
wav = voice.to_audio(text)
pydub_wav = AudioSegment.from_file_using_temporary_files(BytesIO(wav))
audio_length = len(pydub_wav) / 1000
return wav, audio_length
def setUp(self):
self.effects = {
eff_class: set()
for eff_class in (PhonemicEffect, TextEffect, AudioEffect,
VoiceEffect)
}
for effect_cls in set(AVAILABLE_EFFECTS):
effect = effect_cls()
for cls in self.effects.keys():
if isinstance(effect, cls):
self.effects[cls].add(effect)
self.voice = Voice(lang="fr")
def __init__(self, filepath: str, lang="fr"):
self.voice = Voice(lang=lang)
self.alphabet = bidict({pho : i for i, pho in enumerate(self.voice.phonems._all | {"_"})})
self.alphabet_size = len(self.alphabet)
logging.info("Loading the input file")
with open(filepath) as corpus_file:
phonemized_file = PhonemeList(corpus_file.read())
self.synth = Synthesizer(self._build_phonemes_stats(phonemized_file), self.alphabet, self.voice)
self.phonemes_list = [phoneme.name for phoneme in phonemized_file]
def get_phonemes(utterance, lang="en", arpabet=True, default_dur=0.4):
try:
#raise
from voxpopuli import Voice
voice = Voice(lang=lang)
print(voice.to_phonemes(utterance))
if arpabet:
return [(ipa2arpabet[phoneme.name.replace("_",
".")], phoneme.duration)
for phoneme in voice.to_phonemes(utterance)]
else:
return [(phoneme.name.replace("_", "pau"), phoneme.duration)
for phoneme in voice.to_phonemes(utterance)]
except:
phones = fallback_get_phonemes(utterance, lang).split()
# some cleanup, remove digits
phones = [pho.strip("0123456789") for pho in phones]
if not arpabet:
phones = [arpabet2ipa[pho.replace(".", "_")] for pho in phones]
return [(pho, default_dur) for pho in phones]
class RhymeTree(TreeNode):
def __init__(self, rhyming_lang="fr"):
super().__init__()
self.voice = Voice(lang=rhyming_lang)
self.children = dict() # type:Dict[str,Union[TreeNode, Leaf]]
def insert_rhyme(self, rhyme_string, data=None):
new_leaf = Leaf.from_string(rhyme_string.strip(), self.voice)
if new_leaf is not None:
if data is not None:
new_leaf.data = data
self.insert(new_leaf, 1)
else:
logging.warning("Word '%s' returned empty phoneme" % rhyme_string)
def find_rhyme(self, string):
string_phonemes = Leaf.clean_silences(
[pho.name for pho in self.voice.to_phonemes(string)])
current_pho = string_phonemes.pop()
if current_pho not in self.children:
return None
else:
return self.children[current_pho].find(string_phonemes, string)
def save(self, filepath):
with open(filepath, "wb") as picklefile:
pickle.dump(self, picklefile)
@classmethod
def from_pickle(cls, pickle_filepath):
with open(pickle_filepath, "rb") as picklefile:
return pickle.load(picklefile)
@classmethod
def from_text_file(cls, textfile_filepath, lang="fr", separator=None):
separator = separator if separator is not None else "\n"
with open(textfile_filepath) as file:
all_strings = file.read().split(separator)
return cls.from_word_list(all_strings, lang)
@classmethod
def from_word_list(cls, input_list, lang="fr"):
tree = cls(lang)
for string in input_list:
tree.insert_rhyme(string)
return tree
def to_dict(self):
return {pho: child.to_dict() for pho, child in self.children.items()}
class TestEffects(unittest.TestCase):
text = "Les écoute pas ces sheitane c moi le vrai crysw"
def setUp(self):
self.effects = {
eff_class: set()
for eff_class in (PhonemicEffect, TextEffect, AudioEffect,
VoiceEffect)
}
for effect_cls in set(AVAILABLE_EFFECTS):
effect = effect_cls()
for cls in self.effects.keys():
if isinstance(effect, cls):
self.effects[cls].add(effect)
self.voice = Voice(lang="fr")
def test_text_effects(self):
for effect in self.effects[TextEffect]:
self.assertIsNotNone(effect.process(self.text))
def test_phonemic_effects(self):
pho = self.voice.to_phonemes(self.text)
for effect in self.effects[PhonemicEffect]:
self.assertIsNotNone(effect.process(pho))
def test_audio_effects(self):
wav = self.voice.to_audio(self.text)
_, wav_array = get_event_loop().run_until_complete(
AudioRenderer.to_f32_16k(wav))
for effect in self.effects[AudioEffect]:
self.assertIsNotNone(effect.process(wav_array))
def test_voice_effects(self):
cookie_hash = md5(("parce que nous we").encode('utf8')).digest()
voice_params = VoiceParameters.from_cookie_hash(cookie_hash)
for effect in self.effects[VoiceEffect]:
self.assertIsNotNone(effect.process(voice_params))
def __init__(self, rhyming_lang="fr"):
super().__init__()
self.voice = Voice(lang=rhyming_lang)
self.children = dict() # type:Dict[str,Union[TreeNode, Leaf]]
# import pandas as pd
from voxpopuli import Voice
# taille moyenne des phrases en phonèmes
CORPUS_PATH = "french_corpus.txt"
voice = Voice(lang="fr")
phonemes_count = []
def extract_sentence(corpus):
for x in corpus:
phonetized_sentence = voice.to_phonemes(x)
yield phonetized_sentence.phonemes_str.strip("_")
phonemes_count = []
with open(CORPUS_PATH, "r") as corpus:
for x in extract_sentence(corpus):
phonemes_count.append(len(x))
print(sum(phonemes_count ) / len(phonemes_count))
import pandas as pd
from voxpopuli import Voice
import json
import tqdm
import pprint
lx = pd.read_csv('data/lexique.csv', sep='\t')
filtered_lx = lx[lx['4_cgram'].isin(["NOM", "ADJ", "ADV"])]
dict_pho = {}
v = Voice(lang="fr")
for index, word_row in tqdm.tqdm(filtered_lx.iterrows(),
total=len(filtered_lx)):
mot = word_row["1_ortho"]
try:
phonemes = v.to_phonemes(mot)
except Exception as e:
print(e)
print(mot)
continue
pho_list = []
for pho in phonemes:
if pho.name != "_":
pho_list.append(pho.name)
if len(pho_list) > 1:
word_data = {
"pho": pho_list,
"gram": word_row["4_cgram"],
beat_duration = len(beats_track) / (rate * BEATS_TRACK_BEAT_COUNT)
beats_track_looped = np.tile(
beats_track,
LOOPS_COUNT * BEATS_PER_MEASURE * len(CHORDS_PROGRESSION) //
BEATS_TRACK_BEAT_COUNT)
logging.info("Beat time : %dms" % (beat_duration * 1000))
logging.info("Measure time : %dms" % (beat_duration * 1000 * 4))
prog_freqs = get_trinote_progression_freqs(CHORDS_PROGRESSION)
logging.info("First freq progression: \n %s" % (str(prog_freqs)))
track_freqs = prog_freqs * LOOPS_COUNT
progression_phonems = PhonemeList([])
for freq in track_freqs:
progression_phonems.append(
Phoneme("a", int(beat_duration * 1000), [(0, freq), (100, freq)]))
logging.info("Rendering audio")
voice = Voice(lang="fr", voice_id=2)
wav = voice.to_audio(progression_phonems)
if BEATS_TRACK_FILE is not None:
rate, wave_array = to_f32_16k(wav)
mixed_tracks = mix_tracks(beats_track_looped * 0.6,
wave_array * 0.3,
align="left")
wav = to_wav_bytes(mixed_tracks, 16000)
player = AudioPlayer()
player.set_file(BytesIO(wav))
player.play()
player.close()
#print(len(phoneme.pitch_modifiers))
phoneme.duration = notearr[vnum][1]
for pnum, pimo in enumerate(phoneme.pitch_modifiers, start=0):
if notearr[vnum][0] != '_':
phoneme.pitch_modifiers[pnum] = (pimo[0], notearr[vnum][0])
vnum += 1
#print(phoneme)
#print("---")
print(phonemes_list)
if fname != None:
voice.to_audio(phonemes_list, fname)
voice.say(phonemes_list)
# Sing in German: "Alle meine Entchen"
voice = Voice(lang="de", voice_id=2)
text = "Alle meine Entchen schwimmen auf dem See. | schwimmen auf dem See. | Köpfchen in das Wasser. Schwänzchen in die Höh."
notes = 'd4 e4 f#4 g4 a2 a2 b4 b4 b4 b4 a2 4 b4 b4 b4 b4 a2 4 g4 g4 g4 g4 f#2 f#2 a4 a4 a4 a4 d2'
sing(text, notes, voice, "entchen.wav")
# Sing "Atemlos"
voice = Voice(lang="de", voice_id=5)
text = "Atemlos durch die Nacht | bis ein neuer Tag erwacht."
notes = '+c4 b4 a2 a4 g8 e2 8 e4 g8 g4. -b8 b4. b4 c4.'
# if you don't specify a filename, you sing without saving:
sing(text, notes, voice)
# Sing in French: "Frère Jacques"
voice = Voice(lang="fr", voice_id=1)
# in the text Jacques is changed by Jacquès and matines by matinès for the purpose of singing..
text = "Frèrè Jacquès, Frèrè Jacquès, dormez-vous, dormez-vous? Sonnez les matinès, sonnez les matinès, Ding, ding, dong. Ding, ding, dong."
def get_voice(self):
return Voice(lang=self.lang, pitch=self.pitch, speed=self.speed,
voice_id=self.voice_id, volume=self.volume)
beats_track_looped = np.tile(beats_track,
PROG_LOOP_COUNT * BEATS_PER_MEASURE * FULL_LOOP_COUNT * \
(FIRST_PROG_REPEAT + SECOND_PROG_REPEAT) // BEATS_TRACK_BEAT_COUNT)
logging.info("Beat time : %dms" % (beat_duration * 1000))
logging.info("Measure time : %dms" % (beat_duration * 1000 * 4))
first_prog_freqs = get_trinote_progression_freqs(FIRST_CHORDS_PROGRESSION)
logging.info("First freq progression: \n %s" % (str(first_prog_freqs)))
second_prog_freqs = get_trinote_progression_freqs(SECOND_CHORDS_PROGRESSION)
logging.info("First freq progression: \n %s" % (str(second_prog_freqs)))
track_freqs = first_prog_freqs * FIRST_PROG_REPEAT + second_prog_freqs * SECOND_PROG_REPEAT
progression_phonems = PhonemeList([])
for freq in track_freqs * FULL_LOOP_COUNT:
progression_phonems.append(
Phoneme("w", int(beat_duration * 1000), [(0,freq), (100,freq)])
)
logging.info("Rendering audio")
voice = Voice(lang="fr", voice_id=3)
wav = voice.to_audio(progression_phonems)
if BEATS_TRACK_FILE is not None:
rate, wave_array = to_f32_16k(wav)
mixed_tracks = mix_tracks(beats_track_looped * 0.6, wave_array * 0.4, align="left")
wav = to_wav_bytes(mixed_tracks, 16000)
player = AudioPlayer()
player.set_file(BytesIO(wav))
player.play()
player.close()
syllablebuffer.append(pho)
elif pho in FrenchPhonemes.VOWELS:
syllablebuffer.append(pho)
syllabe = "".join(syllablebuffer)
syllabe_list.append(syllabe)
syllablebuffer = []
#si le syllablebuffer n'est pas vide on ajoute les phonèmes à la dernière syllabe
if syllablebuffer:
syllabe_list[-1] += "".join(syllablebuffer)
return syllabe_list
if __name__ == "__main__":
args = parser.parse_args()
v = Voice(lang="fr")
phonemes = v.to_phonemes(args.query)
pho_query = []
for pho in phonemes:
if pho.name != "_":
pho_query.append(pho.name)
rimes = []
for mot, word_data in lexicon.items():
pho_list = word_data['pho']
# Depending on the argument selected by the user regarding grammatical class, genre, number,
# certain words are 'skipped'.
if args.gram is not None and word_data['gram'] not in args.gram: