build_en_foreign_accents.py

import os
import numpy as np
import soundfile
import msinference

foreign_accents_en = os.listdir('assets/wavs/mimic3_foreign/') # build by mimic3 USE assets/wavs/style_vector/ for native
foreign_accents_en = sorted(foreign_accents_en)




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 : FOREIGN ACCENTS
       
          or   
          
       voice : 'deu'  # from LHS code -> https://huggingface.co/dkounadis/artificial-styletts2/blob/main/Utils/all_langs.csv
       '''

    # StyleTTS2 - English
    
    # 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,
                                    alpha=0.3,
                                    beta=0.7,
                                    diffusion_steps=7,
                                    embedding_scale=1)
        
    # mimic-3 format of voice (English text - Foreign accent)    
        
    elif '_' in voice:  # MSS-TTS dont have '_' HOWEVER all assets/wavs/mimic3_foreign_4x have '_'
        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,
                                    alpha=0.3,
                                    beta=0.7,
                                    diffusion_steps=7,
                                    embedding_scale=1)
    

    # 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

ONLY_PARSE_TABLE = False  # also generate .wavs if not already uploaded to issue and links are taken
if not ONLY_PARSE_TABLE:
    from pathlib import Path
    Path('foreign_accents_en_dir/').mkdir(parents=True, exist_ok=True)

    for v in foreign_accents_en:
        _str = v[:-4]  # strip .wav
        print(_str)
        try:
            soundfile.write('foreign_accents_en_dir/' + v, tts_entry(voice=_str), 24000)
            # checkt out folder to count all phonemized voices
        except RuntimeError:
                # return F.conv2d(input, weight, bias, self.stride,  # ENGLISH letters not phonemisable for this ACCENT/LANG
                # RuntimeError: Calculated padded input size per channel: (5 x 4). Kernel size: (5 x 5). Kernel size can't be greater than actual input size
            print('SKIP', _str)



# --------------------------------------------------- Uploads in hf issue
upload_wav = ['<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/tcnoTH-oHKC582O_LFlWF.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/lsMnciJ8SjdVHHm7r3fWj.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/PCvruWc3TeGrQT49Ysx7m.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/0phadlvni_1Wqpaontq0R.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/OpDULPOgboiwGdSdJNp9N.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/rFte6QmNZZ68RVD5rK10n.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/Zrvwb3uGTXXQzbiJjMAKD.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/Sg8TwofY5T_NcleMzkSrR.wav"></audio>',
'<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/65ae91633db2280ece0a6b02/5si01GF0nkn-Gz0x6nesw.wav"></audio>',
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tmp = '<table><tr><th>  </th><th> voice </th><th>  TTS </th></tr>'
for j, (voice, _f) in enumerate(zip(sorted(os.listdir('foreign_accents_en_dir/')), upload_wav)):
    tmp += f'<tr>\n<td>\n\n{j}\n\n</td>\n<td>\n\n  {voice[:-4]}  \n\n</td>\n<td>\n\n  {_f}  \n\n</td>\n</tr>\n'
    
tmp += '\n\n</table>'    
with open('table_for_issue_accents_upload.txt', 'w') as f:
    f.write(tmp)