o Si@s@dZddlZddlZddlmZddlmZddlmZddl m Z ddl m Z m Z mZmZmZmZmZddlmZdd lmZmZmZdd lmZmZmZdd lmZmZdd l m!Z!m"Z"d Z#   dde!dee$ee$fdee!de%de e$e e$eeeffff ddZ&de de dedeee e$eefffddZ'dS)aJ Description taken from the official website of wenetspeech (https://wenet-e2e.github.io/WenetSpeech/) We release a 10000+ hours multi-domain transcribed Mandarin Speech Corpus collected from YouTube and Podcast. Optical character recognition (OCR) and automatic speech recognition (ASR) techniques are adopted to label each YouTube and Podcast recording, respectively. To improve the quality of the corpus, we use a novel end-to-end label error detection method to further validate and filter the data. See https://github.com/wenet-e2e/WenetSpeech for more details about WenetSpeech N) defaultdict)ProcessPoolExecutor)repeat)Path)AnyDictListOptionalSequenceTupleUnion)tqdm)compute_num_samples fix_manifests$validate_recordings_and_supervisions) AudioSource Recording RecordingSet)SupervisionSegmentSupervisionSet)Pathlike add_durations)LMSDEVTEST_NET TEST_MEETINGall corpus_dir dataset_parts output_dirnum_jobsreturnc Cst|}|sJd||durt|}|jdddd|vr$tn|}tt}|D]}|tvr9td|ggd||<q,|d}|sPJd |t d |t t |d d d }t |8} t| t|dt|t|ddD]\} } | D]} || d| || d| | qqyWdn1swY|D]?}tt||dt||dd\} }t| |d|dur||d|d| |d|d| |d||<q|S)a Returns the manifests which consist of the Recordings and Supervisions :param corpus_dir: Pathlike, the path of the data dir. :param dataset_parts: Which parts of dataset to prepare, all for all the parts. :param output_dir: Pathlike, the path where to write the manifests. :num_jobs Number of workers to extract manifests. :return: a Dict whose key is the dataset part, and the value is Dicts with the keys 'recordings' and 'supervisions'. zNo such directory: NT)parentsexist_okrz)No such part of dataset in WenetSpeech : ) recordings supervisionszWenetSpeech.jsonzNo such file : zLoading raw manifests from : rutf8)encodingaudiosz#Processing WenetSpeech JSON entries)descr'r(wenetspeech_supervisions_z .jsonl.gzwenetspeech_recordings_)ris_dirmkdirWETNET_SPEECH_PARTSrdict ValueErroris_filelogginginfojsonloadopenrr mapparse_utterancerappendextendrrfrom_recordingsr from_segmentsrto_file)r r!r"r#subsets manifestssubraw_manifests_path raw_manifestsex recordingsegmentspartr'r(rKO/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/recipes/wenet_speech.pyprepare_wenet_speech%s`    rMaudio root_pathrBc Csd}t|dtddgt||ddgt|d|d||dd }tt}|D]}g||<q(|d D]2}t|d |d|d t|d |d  |dd|dd}|dD] }||vrd|| |qWq3||fS)Ni>aidfilerpath)typechannelssourceduration)rV sampling_rate)idsources num_samplesrWrVrIsid begin_timeend_time)rWChinesetext)rX recording_idstartrVlanguager_rB) rrstrrrr3rrstripr=) rNrOrBrWrHrIrDsegsegmentrKrKrLr<msF    r<)rNr)(__doc__r8r6 collectionsrconcurrent.futuresr itertoolsrpathlibrtypingrrrr r r r tqdm.autor lhotserrr lhotse.audiorrrlhotse.supervisionrr lhotse.utilsrrr2rcintrMr<rKrKrKrLsJ    $  H