o SiI(@sdZddlZddlZddlZddlZddlZddlmZddlm Z ddl m Z m Z m Z mZddlmZddlmZddlmZmZmZdd lmZmZdd lmZmZgd Zd d eDZeeddZ gdZ!dgZ"e!Z#gd Z$gdZ%dZ&  d.dede e'de fddZ(      d/dede ede'd e'd!e e'd"e e'd#e)de e'e e'eeeffffd$d%Z*Gd&d'd'Z+ d0de de d e'd#e)de e'e e'eeeffff d(d)Z,de d!e'd"e'de eeffd*d+Z-de d e'de edffd,d-Z.dS)1uI VoxPopuli provides - 400K hours of unlabelled speech data for 23 languages - 1.8K hours of transcribed speech data for 16 languages - 17.3K hours of speech-to-speech interpretation data for 15x15 directions - 29 hours of transcribed speech data of non-native English intended for research in ASR for accented speech (15 L2 accents) The raw data is collected from 2009-2020 European Parliament event recordings. For details about the corpus, please refer to the website: https://github.com/facebookresearch/voxpopuli Reference: Wang, Changhan et al. “VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation.” Annual Meeting of the Association for Computational Linguistics (2021). This script is based on code from the repository linked above. NOTE: Our data preparation is slightly different from the original repository. In particular, we only use the metadata to create manifests, i.e., we do not create segment-level wav files, unlike the original repository. In this way, we can avoid duplicating the audio files. N) defaultdict)Path)DictOptionalTupleUnion)download_url_to_file)tqdm) RecordingSetSupervisionSegmentSupervisionSet) fix_manifests$validate_recordings_and_supervisions)Pathlike safe_extract)endefresplitrohucsnlfihrsksletltptbgellvmtsvdacCg|]}|dqS)_v2.0xr*r*L/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/recipes/voxpopuli.py .r/ii)rrrrrrrrrrrrrrrr en_accented)rrrz(https://dl.fbaipublicfiles.com/voxpopuli.asr target_dirsubsetreturnc Cs\t|}|jddd|tvr!|ddg}tddtD}n*|tvr+|g}t}n tttdgd|d }td dtDtd d gtd|d }g}|D]}|D]}|td |d|dqSqO|d}|jdddt t |dt |D]-}|t|j } t|| t| d } t| |Wd n1swY| q~|S)aw Download and untar/unzip the VoxPopuli dataset. :param target_dir: Pathlike, the path of the dir to storage the dataset. :param subset: str, the subset of the dataset to download, can be one of "400k", "100k", "10k", "asr", or any of the languages in LANGUAGES or LANGUAGES_V2. :return: the path to downloaded and extracted directory with data. T)parentsexist_ok_rcSr(_2r*r,yr*r*r.r/Xr0z&download_voxpopuli..original)400k100k10kr3NcSr(r:r*r<r*r*r.r/dr0iiz/audios/z.tar raw_audiosr8r7z files to download...r)rmkdir LANGUAGES_V2splitYEARS LANGUAGESgetappendDOWNLOAD_BASE_URLlogginginfolenr namertarfileopenrunlink) r4r5 languagesyearsurl_listlr=out_rooturltar_pathtar_filer*r*r.download_voxpopuliGsL     r\r corpus_dir output_dirtasklang source_lang target_langnum_jobsc Cst|}|sJd||durt|}|jddd|dkr6|tvs-Jd|t||||d}n5|dkrW|tvsEJd ||tvsPJd |t|||}n|d krk|tvsfJd|t||}| D]R\}} t di| \} } t | | d | ||d <| ||d<|dkr|d|n|} |dur| |d|d| d|d| |d|d| d|dqo|S)aY Prepares and returns the VoxPopuli manifests which consist of Recordings and Supervisions. :param corpus_dir: Pathlike, the path of the data dir. :param output_dir: Pathlike, the path where to write the manifests. :param task: str, the task to prepare the manifests for, can be one of "asr", "s2s", "lm". :param lang: str, the language to prepare the manifests for, can be one of LANGUAGES or LANGUAGES_V2. This is used for "asr" and "lm" tasks. :param source_lang: str, the source language for the s2s task, can be one of S2S_SRC_LANGUAGES. :param target_lang: str, the target language for the s2s task, can be one of S2S_TGT_LANGUAGES. :param num_jobs: int, the number of parallel jobs to use for preparing the manifests. :return: Dict[str, Dict[str, Union[RecordingSet, SupervisionSet]]], the manifests. zNo such directory: NTrCr3zUnsupported language: )rds2szUnsupported source language: zUnsupported target language: lm) recordings supervisionsrgrh-z voxpopuli- _recordings_z .jsonl.gz_supervisions_r*) ris_dirrE ASR_LANGUAGES_prepare_voxpopuli_asrS2S_SRC_LANGUAGESS2S_TGT_LANGUAGES_prepare_voxpopuli_s2s_prepare_voxpopuli_lmitemsr rto_file) r^r_r`rarbrcrd manifestskvrgrh lang_affixr*r*r.prepare_voxpopuli|sL     ryc@s0eZdZdZdefddZdedefddZd S) RecordingIdFnz This functor class avoids error in multiprocessing: `AttributeError: Can't pickle local object '_prepare_voxpopuli_asr..'` languagecCs ||_dSNr{)selfr{r*r*r.__init__s zRecordingIdFn.__init__pathr6cCs,td|jdd|j}tdd|}|S)Nr9$z _original$)resubr{stem)r~r recording_idr*r*r.__call__szRecordingIdFn.__call__N)__name__ __module__ __qualname____doc__strrrrr*r*r*r.rzsrzcstd|d|}tj|d|t|dd}td|d}|t|j}|s;td|d |t ||ntd |t |d }d d t j |ddD} Wdn1s`wYtt} tdd} t| D]Q} | ddvr~qs| d} t| d}t| d|}| | d7<| t| d| | | t|ddt|ddd|| d| d| dd | d!id" qstt| D]\}ttd#d |D<qtt}dD]|fd$d|d%<t| |d&<q|S)'zG Download metadata TSV and prepare manifests for the ASR task. z5Preparing recordings (this may take a few minutes)...rBz*.oggr})rdrz/annotations/asr/asr_z.tsv.gzzDownloading : z -> z!Using pre-downloaded annotations rtcSsg|]}|qSr*r*r+r*r*r.r/sz*_prepare_voxpopuli_asr..|) delimiterNcSsdS)Nrr*r*r*r*r.sz(_prepare_voxpopuli_asr..rG)traindevtest session_id start_timeend_timer]ri)ndigitsr speaker_idgender normed_text orig_text original_text) idrstartdurationchannelr{speakerrtextcustomcSsg|]}|jqSr*)r)r,sr*r*r.r/scs|jvSr|)r)rDreco_idsrGr*r.rsrgrh)rMrNr from_dirrzrLrrPexistsrgziprRcsv DictReaderrlistr floatrKr roundrssortedsetdictfilterr from_segments)r^r_rardin_rootrgrYtsv_pathfmetadatasegments num_segmentsrDreco_idrrsegsrur*rr.rnsh           rncCt)z1 Prepare the manifests for the s2s task. NotImplementedError)r^rbrcr*r*r.rqsrqcCr)z0 Prepare the manifests for the lm task. r)r^rar*r*r.rr$srr)r2r3)Nr3rNNr])r])/rrrrMrrQ collectionsrpathlibrtypingrrrr torch.hubrr lhotser r r lhotse.qar r lhotse.utilsrrrIrFrrangerHrmASR_ACCENTED_LANGUAGESrorp*S2S_TGT_LANGUAGES_WITH_HUMAN_TRANSCRIPTIONrLrr\intryrzrnrqrrr*r*r*r.s     7 B N  "