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import numpy as np
import soundfile
import msinference
def tts_entry(text='A quick brown fox jumps over the lazy dog. Sweet dreams are made of this, I traveled the world and the seven seas.',
voice='af_ZA_google-nwu_1919', # 'serbian', # 'en_US/vctk_low#p276', 'isl', 'abi',
speed=1.4, # only for non-english
affect = True # False = high clarity for partially sight
):
'''returns 24kHZ np.array TTS
voice : 'en_US/vctk_low#p276' # from English voices -> https://audeering.github.io/shift/
or
voice : 'af_ZA_google-nwu_1919' # from english non-native accents -> https://huggingface.co/dkounadis/artificial-styletts2/discussions/1#6783e3b00e7d90facec060c6
or
voice : 'deu' # foreign langs -> https://huggingface.co/dkounadis/artificial-styletts2/blob/main/Utils/all_langs.csv
'''
# StyleTTS2 - En
# mimic-3 format of voice (English txt - English accent)
if ('en_US/' in voice) or ('en_UK/' in voice):
a = '' if affect else 'v2/'
style_vector = msinference.compute_style('assets/wavs/style_vector/' + a + voice.replace(
'/', '_').replace('#', '_').replace(
'cmu-arctic', 'cmu_arctic').replace(
'_low', '') + '.wav')
x = msinference.inference(text,
style_vector)
# mimic-3 format of voice (English text - Foreign accent)
elif '_' in voice:
style_vector = msinference.compute_style('assets/wavs/mimic3_foreign_4x/' + voice.replace(
'/', '_').replace('#', '_').replace(
'cmu-arctic', 'cmu_arctic').replace(
'_low', '') + '.wav')
x = msinference.inference(text,
style_vector)
# Fallback - MMS TTS - Non-English
else:
# dont split foreign sentences: Avoids re-load of VITS & random speaker change issue
x = msinference.foreign(text=text,
lang=voice, # voice = 'romanian', 'serbian' 'hungarian'
speed=speed) # normalisation externally
# volume
x /= np.abs(x).max() + 1e-7 # amplify speech to full [-1,1]
print(x.shape, 'TTS OK')
return x
soundfile.write(f'demo.wav', tts_entry(), 24000)
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