o Si @sdZddlZddlZddlmZddlmZmZmZm Z ddl m Z m Z ddl mZmZddlmZmZddlmZd Zd ed efd d Zded eeeeffddZddefdedeedeed efddZdefddZ  d dedeeded e eeffddZdS)!aA About the Earnings 22 dataset: The Earnings 22 dataset ( also referred to as earnings22 ) is a 119-hour corpus of English-language earnings calls collected from global companies. The primary purpose is to serve as a benchmark for industrial and academic automatic speech recognition (ASR) models on real-world accented speech. This dataset has been submitted to Interspeech 2022. The paper describing our methods and results can be found on arXiv at https://arxiv.org/abs/2203.15591. @misc{https://doi.org/10.48550/arxiv.2203.15591, doi = {10.48550/ARXIV.2203.15591}, url = {https://arxiv.org/abs/2203.15591}, author = {Del Rio, Miguel and Ha, Peter and McNamara, Quinten and Miller, Corey and Chandra, Shipra}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Earnings-22: A Practical Benchmark for Accents in the Wild}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution Share Alike 4.0 International} } N)Path)DictListOptionalUnion) fix_manifests$validate_recordings_and_supervisions) Recording RecordingSet)SupervisionSegmentSupervisionSet)Pathlikez,https://github.com/revdotcom/speech-datasetstextreturncCs"|tddtj}|}|S)N) translatestr maketransstring punctuationlower)rrM/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/recipes/earnings22.py normalize'srpathcCsft|%}|t}|D]}|d}|dd||d<q|WdS1s,wYdS)N,r)openreadlinedictsplit)rfoutlinerrr read_metadata/s  $r%.F target_dirforce_downloadurlcCs"tddtddddS)aGDownload and untar the dataset. :param target_dir: Pathlike, the path of the dir to store the dataset. The extracted files are saved to target_dir/earnings22/ Please note that the github repository contains other additional datasets and using this call, you will be downloading all of them and then throwing them out. :param force_download: Bool, if True, download the tar file no matter whether it exists or not. :param url: str, the url to download the dataset. :return: the path to downloaded and extracted directory with data. zBDownloading Earnings22 from github repository is not implemented. z Please visit z) and download the files manually. Please zGfollow the instructions closely as you need to use git-lfs to download zsome of the audio files.N)loggingerror _DEFAULT_URL)r'r(r)rrrdownload_earnings229s r-filenamecCs`t|"}t}||D]}|d}||dq|WdS1s)wYdS)N|r)rlistrr!append)r.r" transcriptr$rrrparse_nlp_filePs  $r3 corpus_dir output_dirnormalize_textc Csnt|}|sJd||durt|}|jddd|d}t|d}t|dks1J|tdd |D}|d d }t|d }t|dksTJt |d }|t} |D],} | j } d t | } |rut | } t| | d|| jdd|| d| d} | | qct| }t||\}}t|||dur||d||d||fS)ay Returns the manifests which consist of the Recordings and Supervisions. When all the manifests are available in the ``output_dir``, it will simply read and return them. :param corpus_dir: Pathlike, the path of the data dir. The structure is expected to mimic the structure in the github repository, notably the mp3 files will be searched for in [corpus_dir]/media and transcriptions in the directory [corpus_dir]/transcripts/nlp_references :param output_dir: Pathlike, the path where to write the manifests. :param normalize_text: Bool, if True, normalize the text. :return: (recordings, supervisions) pair .. caution:: The `normalize_text` option removes all punctuation and converts all upper case to lower case. This includes removing possibly important punctuations such as dashes and apostrophes. zNo such directory: NT)parentsexist_okmediaz*.mp3}css|]}t|VqdS)N)r from_file).0prrr ~s  z%prepare_earnings22.. transcriptsnlp_referencesz*.nlpz metadata.csv grzEnglish-)id recording_idstartdurationchannellanguagerz$earnings22_supervisions_all.jsonl.gzz"earnings22_recordings_all.jsonl.gz)ris_dirmkdirr0globlensortr from_recordingsr%stemjoinr3rr rFr1r from_segmentsrrto_file)r4r5r6 media_dir audio_files recording_setnlp_dir nlp_filesmetadatasupervision_segmentsnlp_filerCrssupervision_setrrrprepare_earnings22ZsP     r])NF)__doc__r*rpathlibrtypingrrrrlhotserr lhotse.audior r lhotse.supervisionr r lhotse.utilsr r,rrr%boolr-r3r]rrrrsH