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from torch.utils.data import ConcatDataset
from Architectures.Aligner.autoaligner_train_loop import train_loop as train_aligner
from Utility.corpus_preparation import prepare_aligner_corpus
from Utility.path_to_transcript_dicts import *
from Utility.storage_config import MODELS_DIR
from Utility.storage_config import PREPROCESSING_DIR
def run(gpu_id, resume_checkpoint, finetune, model_dir, resume, use_wandb, wandb_resume_id, gpu_count):
if gpu_id == "cpu":
device = torch.device("cpu")
else:
device = torch.device("cuda")
if gpu_count > 1:
rank = int(os.environ["LOCAL_RANK"])
torch.cuda.set_device(rank)
torch.distributed.init_process_group(backend="nccl")
else:
rank = 0
print("Preparing")
datasets = list()
lang_id = "afr"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_afr(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_afr"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "nso"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_nso(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_nso"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sot"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_sot(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_sot"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ssw"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_ssw(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_ssw"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tsn"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_tsn(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_tsn"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tso"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_tso(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_tso"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ven"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_ven(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_ven"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "xho"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_xho(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_xho"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "zul"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nchlt_zul(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nchlt_zul"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bem"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_bembaspeech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "bembaspeech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "swh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_alffa_sw(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "alffa_sw"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "amh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_alffa_am(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "alffa_am"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "wol"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_alffa_wo(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "alffa_wo"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mal"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_malayalam(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "malayalam"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mal"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_msc(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "msc"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "chv"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_chuvash(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "chuvash"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "iba"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_iban(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "iban"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sun"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_sundanese_speech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "sundanese_speech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_sinhala_speech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "sinhala_speech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ben"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_bengali_speech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "bengali_speech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "npi"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nepali_speech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "nepali_speech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "jav"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_javanese_speech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "javanese_speech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "fon"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_fon_alf(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_fon_alf"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hau"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_hausa_cmv(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_hausa_cmv"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lbb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_ibibio_lst(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_ibibio_lst"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kik"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_kikuyu_opb(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_kikuyu_opb"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_lingala_opb(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_lingala_opb"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lug"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_ganda_cmv(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_ganda_cmv"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "luo"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_luo_afv(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_luo_afv"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "luo"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_luo_opb(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_luo_opb"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "swh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_swahili_llsti(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_swahili_llsti"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sxb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_suba_afv(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_suba_afv"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "wol"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_wolof_alf(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_wolof_alf"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "yor"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_african_voices_yoruba_opb(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "african_voices_yoruba_opb"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "nya"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_zambezi_voice_nyanja(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "zambezi_voice_nyanja"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "loz"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_zambezi_voice_lozi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "zambezi_voice_lozi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "toi"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_zambezi_voice_tonga(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "zambezi_voice_tonga"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "afr"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_afrikaans(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_afrikaans"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "amh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_amharic(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_amharic"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "arb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_arabic(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_arabic"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "asm"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_assamese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_assamese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ast"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_asturian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_asturian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "azj"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_azerbaijani(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_azerbaijani"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bel"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_belarusian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_belarusian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bul"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_bulgarian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_bulgarian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ben"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_bengali(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_bengali"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bos"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_bosnian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_bosnian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "cat"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_catalan(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_catalan"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ceb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_cebuano(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_cebuano"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sdh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_sorani_kurdish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_sorani_kurdish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "cmn"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_mandarin(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_mandarin"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ces"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_czech(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_czech"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "cym"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_welsh(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_welsh"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "dan"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_danish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_danish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "deu"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_german(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_german"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ell"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_greek(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_greek"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "eng"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_english(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_english"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "spa"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_spanish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_spanish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ekk"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_estonian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_estonian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pes"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_persian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_persian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "ful"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_fula(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_fula"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "fin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_finnish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_finnish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "fil"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_filipino(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_filipino"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "fra"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_french(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_french"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "gle"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_irish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_irish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "glg"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_galician(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_galician"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "guj"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_gujarati(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_gujarati"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hau"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_hausa(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_hausa"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "heb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_hebrew(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_hebrew"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_hindi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_hindi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hrv"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_croatian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_croatian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hun"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_hungarian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_hungarian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hye"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_armenian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_armenian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ind"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_indonesian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_indonesian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ibo"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_igbo(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_igbo"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "isl"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_icelandic(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_icelandic"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ita"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_italian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_italian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "jpn"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_japanese(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_japanese"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "jav"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_javanese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_javanese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kat"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_georgian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_georgian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kam"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_kamba(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_kamba"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kea"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_kabuverdianu(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_kabuverdianu"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kaz"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_kazakh(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_kazakh"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "khm"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_khmer(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_khmer"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kan"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_kannada(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_kannada"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kor"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_korean(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_korean"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "kir"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_kyrgyz(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_kyrgyz"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "ltz"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_luxembourgish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_luxembourgish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lug"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_ganda(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_ganda"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_lingala(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_lingala"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lao"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_lao(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_lao"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lit"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_lithuanian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_lithuanian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "luo"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_luo(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_luo"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "lvs"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_latvian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_latvian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mri"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_maori(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_maori"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mkd"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_macedonian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_macedonian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mal"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_malayalam(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_malayalam"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "xng"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_mongolian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_mongolian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mar"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_marathi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_marathi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "zsm"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_malay(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_malay"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mlt"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_maltese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_maltese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "mya"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_burmese(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_burmese"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
# lang_id = "nob"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_norwegian(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_norwegian"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
# lang_id = "npi"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_nepali(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_nepali"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "nld"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_dutch(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_dutch"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sot" # technically incorrect, this is the shorthand for southern sotho, but it seems northerns sotho is not in out list.
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_northern_sotho(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_northern_sotho"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "nya"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_nyanja(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_nyanja"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "oci"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_occitan(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_occitan"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "orm"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_oroma(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_oroma"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "ory"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_oriya(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_oriya"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pan"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_punjabi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_punjabi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pol"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_polish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_polish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pst"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_pashto(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_pashto"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "por"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_portuguese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_portuguese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ron"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_romanian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_romanian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "rus"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_russian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_russian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "snd"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_sindhi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_sindhi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "slk"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_slovak(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_slovak"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "slv"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_slovenian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_slovenian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "sna"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_shona(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_shona"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "som"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_somali(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_somali"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "srp"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_serbian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_serbian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "swe"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_swedish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_swedish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "swh"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_swahili(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_swahili"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tam"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_tamil(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_tamil"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tel"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_telugu(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_telugu"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tgk"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_tajik(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_tajik"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "tha"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_thai(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_thai"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "tur"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_turkish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_turkish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "urk"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_ukrainian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_ukrainian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "umb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_umbundu(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_umbundu"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "urd"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_urdu(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_urdu"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "uzn"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_uzbek(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_uzbek"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "vie"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_vietnamese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_vietnamese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "wol"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_wolof(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_wolof"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "xho"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_xhosa(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_xhosa"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "yor"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_yoruba(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_yoruba"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "yue"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_cantonese(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_cantonese"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
# lang_id = "zul"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_fleurs_zulu(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "fleurs_zulu"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "gle"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_living_audio_dataset_irish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "living_audio_dataset_irish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "nld"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_living_audio_dataset_dutch(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "living_audio_dataset_dutch"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "rus"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_living_audio_dataset_russian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "living_audio_dataset_russian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ron"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_romanian_db(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "romanian_db"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pes"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_shemo(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "shemo"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "eng"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mslt_english(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "mslt_english"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "jpn"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mslt_japanese(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "mslt_japanese"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "cmn"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mslt_chinese(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "mslt_chinese"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "hin"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_rajasthani_hindi_speech(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "rajasthani_hindi_speech"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "eng"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_cmu_arctic(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "cmu_arctic"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
# lang_id = "tat"
# datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_sevil_tatar(),
# corpus_dir=os.path.join(PREPROCESSING_DIR, "sevil_tatar"),
# lang=lang_id,
# gpu_count=gpu_count,
# rank=rank, device=device))
lang_id = "arb"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_clartts(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "clartts"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bhd"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_bhadrawahi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_bhadrawahi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kfs"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_bilaspuri(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_bilaspuri"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "dgo"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_dogri(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_dogri"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "gbk"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_gaddi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_gaddi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bgc"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_haryanvi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_haryanvi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "hin"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_hindi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_hindi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "xnr"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_kangri(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_kangri"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kan"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_kannada(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_kannada"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kfx"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_kulvi(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_kulvi"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "kfx"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_kulvi_outer_seraji(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_kulvi_outer_seraji"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mal"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_malayalam(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_malayalam"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "mjl"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_mandeali(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_mandeali"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "bfz"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_pahari_mahasui(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_pahari_mahasui"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tam"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_tamil(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_tamil"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "tel"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_snow_mountain_telugu(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "snow_mountain_telugu"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ukr"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_ukrainian_lada(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "ukrainian_lada"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "deu"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_german(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_german"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "spa"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_spanish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_spanish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "fra"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_french(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_french"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ita"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_italian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_italian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "pol"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_polish(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_polish"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "rus"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_russian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_russian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
lang_id = "ukr"
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_m_ailabs_ukrainian(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "m_ailabs_ukrainian"),
lang=lang_id,
gpu_count=gpu_count,
rank=rank, device=device))
for lang in ["acf", "bss", "deu", "inb", "nca", "quh", "wap", "acr", "bus", "dgr", "ind", "maz", "nch", "qul", "tav", "wmw", "acu", "byr", "dik", "iou", "mbb", "ncj", "qvc", "tbc", "xed", "agd", "bzh", "djk", "ipi", "mbc", "ncl", "qve", "tbg", "xon", "agg", "bzj", "dop", "jac", "mbh", "ncu", "qvh", "tbl", "xtd", "agn",
"caa", "jic", "mbj", "ndj", "qvm", "tbz", "xtm", "agr", "cab", "emp", "jiv", "mbt", "nfa", "qvn", "tca", "yaa", "agu", "cap", "eng", "jvn", "mca", "ngp", "qvs", "tcs", "yad", "aia", "car", "ese", "mcb", "ngu", "qvw", "yal", "cax", "kaq", "mcd", "nhe", "qvz", "tee", "ycn", "ake", "cbc",
"far", "mco", "qwh", "yka", "alp", "cbi", "fra", "kdc", "mcp", "nhu", "qxh", "ame", "cbr", "gai", "kde", "mcq", "nhw", "qxn", "tew", "yre", "amf", "cbs", "gam", "kdl", "mdy", "nhy", "qxo", "tfr", "yva", "amk", "cbt", "geb", "kek", "med", "nin", "rai", "zaa", "apb", "cbu", "glk",
"ken", "mee", "nko", "rgu", "zab", "apr", "cbv", "meq", "nld", "tgo", "zac", "arl", "cco", "gng", "kje", "met", "nlg", "rop", "tgp", "zad", "grc", "klv", "mgh", "nnq", "rro", "zai", "ata", "cek", "gub", "kmu", "mib", "noa", "ruf", "tna", "zam", "atb", "cgc", "guh", "kne",
"mie", "not", "rug", "tnk", "zao", "atg", "chf", "knf", "mih", "npl", "rus", "tnn", "zar", "awb", "chz", "gum", "knj", "mil", "sab", "tnp", "zas", "cjo", "guo", "ksr", "mio", "obo", "seh", "toc", "zav", "azg", "cle", "gux", "kue", "mit", "omw", "sey", "tos", "zaw", "azz", "cme", "gvc", "kvn", "miz",
"ood", "sgb", "tpi", "zca", "bao", "cni", "gwi", "kwd", "mkl", "shp", "tpt", "zga", "bba", "cnl", "gym", "kwf", "mkn", "ote", "sja", "trc", "ziw", "bbb", "cnt", "gyr", "kwi", "mop", "otq", "snn", "ttc", "zlm", "cof", "hat", "kyc", "mox", "pab", "snp", "tte", "zos", "bgt", "con", "kyf", "mpm", "pad",
"som", "tue", "zpc", "bjr", "cot", "heb", "kyg", "mpp", "soy", "tuf", "zpl", "bjv", "cpa", "kyq", "mpx", "pao", "spa", "tuo", "zpm", "bjz", "cpb", "hlt", "kyz", "mqb", "pib", "spp", "tur", "zpo", "bkd", "cpu", "hns", "lac", "mqj", "pir", "spy", "txq", "zpu", "blz", "crn", "hto", "lat", "msy", "pjt", "sri",
"txu", "zpz", "bmr", "cso", "hub", "lex", "mto", "pls", "srm", "udu", "ztq", "bmu", "ctu", "lgl", "muy", "poi", "srn", "ukr", "zty", "bnp", "cuc", "lid", "mxb", "pol", "stp", "upv", "zyp", "boa", "cui", "huu", "mxq", "por", "sus", "ura", "boj", "cuk", "huv", "llg", "mxt", "poy", "suz", "urb", "box",
"cwe", "hvn", "prf", "swe", "urt", "bpr", "cya", "ign", "lww", "myk", "ptu", "swh", "usp", "bps", "daa", "ikk", "maj", "myy", "sxb", "vid", "bqc", "dah", "nab", "qub", "tac", "vie", "bqp", "ded", "imo", "maq", "nas", "quf", "taj", "vmy"]:
datasets.append([prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mms_template(lang=lang),
corpus_dir=os.path.join(PREPROCESSING_DIR, f"mms_{lang}"),
lang=f"{lang}",
gpu_count=gpu_count,
rank=rank, device=device)])
# ENGLISH
chunk_count = 50
chunks = split_dictionary_into_chunks(build_path_to_transcript_dict_mls_english(), split_n=chunk_count)
for index in range(chunk_count):
datasets.append(prepare_aligner_corpus(transcript_dict=chunks[index],
corpus_dir=os.path.join(PREPROCESSING_DIR, f"mls_english_chunk_{index}"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nancy,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Nancy"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_ryanspeech,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Ryan"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_ljspeech,
corpus_dir=os.path.join(PREPROCESSING_DIR, "LJSpeech"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_libritts_all_clean,
corpus_dir=os.path.join(PREPROCESSING_DIR, "libri_all_clean"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_vctk,
corpus_dir=os.path.join(PREPROCESSING_DIR, "vctk"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_nvidia_hifitts,
corpus_dir=os.path.join(PREPROCESSING_DIR, "hifi"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_CREMA_D,
corpus_dir=os.path.join(PREPROCESSING_DIR, "cremad"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_EmoV_DB,
corpus_dir=os.path.join(PREPROCESSING_DIR, "emovdb"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_RAVDESS,
corpus_dir=os.path.join(PREPROCESSING_DIR, "ravdess"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_ESDS,
corpus_dir=os.path.join(PREPROCESSING_DIR, "esds"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_blizzard_2013,
corpus_dir=os.path.join(PREPROCESSING_DIR, "blizzard2013"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_jenny,
corpus_dir=os.path.join(PREPROCESSING_DIR, "jenny"),
lang="eng",
device=device,
gpu_count=gpu_count,
rank=rank))
# GERMAN
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_karlsson,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Karlsson"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_eva,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Eva"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_hokus,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Hokus"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_bernd,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Bernd"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_friedrich,
corpus_dir=os.path.join(PREPROCESSING_DIR, "Friedrich"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_hui_others,
corpus_dir=os.path.join(PREPROCESSING_DIR, "hui_others"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_thorsten_emotional(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "thorsten_emotional"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_thorsten_neutral(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "thorsten_neutral"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_thorsten_2022_10(),
corpus_dir=os.path.join(PREPROCESSING_DIR, "thorsten_2022"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
chunk_count = 10
chunks = split_dictionary_into_chunks(build_path_to_transcript_dict_mls_german(), split_n=chunk_count)
for index in range(chunk_count):
datasets.append(prepare_aligner_corpus(transcript_dict=chunks[index],
corpus_dir=os.path.join(PREPROCESSING_DIR, f"mls_german_chunk_{index}"),
lang="deu",
device=device,
gpu_count=gpu_count,
rank=rank))
# FRENCH
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10fr,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_French"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_french,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_french"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_blizzard2023_ad_silence_removed,
corpus_dir=os.path.join(PREPROCESSING_DIR, "ad_e"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_blizzard2023_neb_silence_removed,
corpus_dir=os.path.join(PREPROCESSING_DIR, "neb"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_blizzard2023_neb_e_silence_removed,
corpus_dir=os.path.join(PREPROCESSING_DIR, "neb_e"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_synpaflex_norm_subset,
corpus_dir=os.path.join(PREPROCESSING_DIR, "synpaflex"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_siwis_subset,
corpus_dir=os.path.join(PREPROCESSING_DIR, "siwis"),
lang="fra",
device=device,
gpu_count=gpu_count,
rank=rank))
# SPANISH
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_spanish,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_spanish"),
lang="spa",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10es,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Spanish"),
lang="spa",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_spanish_blizzard_train,
corpus_dir=os.path.join(PREPROCESSING_DIR, "spanish_blizzard"),
lang="spa",
device=device,
gpu_count=gpu_count,
rank=rank))
# CHINESE
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10cmn,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_chinese"),
lang="cmn",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_aishell3,
corpus_dir=os.path.join(PREPROCESSING_DIR, "aishell3"),
lang="cmn",
device=device,
gpu_count=gpu_count,
rank=rank))
# PORTUGUESE
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_portuguese,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_porto"),
lang="por",
device=device,
gpu_count=gpu_count,
rank=rank))
# POLISH
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_polish,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_polish"),
lang="pol",
device=device,
gpu_count=gpu_count,
rank=rank))
# ITALIAN
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_italian,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_italian"),
lang="ita",
device=device,
gpu_count=gpu_count,
rank=rank))
# DUTCH
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_mls_dutch,
corpus_dir=os.path.join(PREPROCESSING_DIR, "mls_dutch"),
lang="nld",
device=device,
gpu_count=gpu_count,
rank=rank))
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10nl,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Dutch"),
lang="nld",
device=device,
gpu_count=gpu_count,
rank=rank))
# GREEK
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10el,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Greek"),
lang="ell",
device=device,
gpu_count=gpu_count,
rank=rank))
# FINNISH
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10fi,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Finnish"),
lang="fin",
device=device,
gpu_count=gpu_count,
rank=rank))
# VIETNAMESE
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_VIVOS_viet,
corpus_dir=os.path.join(PREPROCESSING_DIR, "VIVOS_viet"),
lang="vie",
device=device,
gpu_count=gpu_count,
rank=rank))
# RUSSIAN
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10ru,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Russian"),
lang="rus",
device=device,
gpu_count=gpu_count,
rank=rank))
# HUNGARIAN
datasets.append(prepare_aligner_corpus(transcript_dict=build_path_to_transcript_dict_css10hu,
corpus_dir=os.path.join(PREPROCESSING_DIR, "css10_Hungarian"),
lang="hun",
device=device,
gpu_count=gpu_count,
rank=rank))
train_set = ConcatDataset(datasets)
save_dir = os.path.join(MODELS_DIR, "Aligner")
os.makedirs(save_dir, exist_ok=True)
save_dir_aligner = save_dir + "/aligner"
os.makedirs(save_dir_aligner, exist_ok=True)
train_aligner(train_dataset=train_set,
device=device,
save_directory=save_dir,
steps=1500000,
batch_size=16,
path_to_checkpoint=resume_checkpoint,
fine_tune=finetune,
debug_img_path=save_dir_aligner,
resume=resume,
gpu_count=gpu_count,
rank=rank,
steps_per_checkpoint=5000) |