o Si:@s8dZddlZddlZddlZddlZddlZddlmZm Z ddl m Z ddl m Z mZmZmZddlZddlZddlZddlmZmZmZddlmZmZddlmZmZmZdd l m!Z!m"Z"dd l#m$Z$d Z%d d Z&ddZ'd?ddZ( d@de$de fddZ)   dAde$de$de$de$dee$de*d e*de e+e e+efffd!d"Z,de$de e+effd#d$Z-d%ed&ee.defd'd(Z/d)ej0d*e*dej0fd+d,Z1d-e2d.ed/ede*dee f d0d1Z3d2ed3ed4e+dee def d5d6Z4d7e dee2fd8d9Z5d:e+d;e de*de dZ6dS)Bag LibriMix dataset preparation for Lhotse. This recipe replicates the LibriMix dataset preparation by manipulating existing recordings instead of generating and saving new audio files. LibriMix is an open source dataset for source separation in noisy environments, derived from LibriSpeech signals (clean subset) and WHAM noise. The original dataset supports: - Multiple sources (2 or 3 speakers) in mixtures - Different sample rates (typically 16kHz and 8kHz) - Different mixture modes: - min: mixture ends when the shortest source ends - max: mixture ends when the longest source ends - Different mixture types: - mix_clean: utterances only - mix_both: utterances + noise - mix_single: 1 utterance + noise **Current Limitations:** This Lhotse recipe currently supports only: - 16kHz sample rate - 'max' mode (mixture ends when the longest source ends) **Important Note on Quantization:** The original LibriMix recipe introduces a quantization error when saving audio files via soundfile, which by default uses PCM_16 format. If you need to replicate the exact quantization behavior from the original recipe, you can apply the following transformation: ```python import tempfile import soundfile as sf with tempfile.NamedTemporaryFile(suffix=".wav") as f: sf.write(f.name, cut.load_audio().T, 16000) audio_quantized, sr = sf.read(f.name) ``` Unlike the original LibriMix generation which creates ~430GB for Libri2Mix and ~332GB for Libri3Mix, this recipe works with existing LibriSpeech and WHAM recordings and creates virtual mixtures, making it much more storage efficient. For more details about LibriMix, see: - GitHub repository: https://github.com/JorisCos/LibriMix/ - Paper: "LibriMix: An Open-Source Dataset for Generalizable Speech Separation" https://arxiv.org/pdf/2005.11262.pdf Citation: @misc{cosentino2020librimix, title={LibriMix: An Open-Source Dataset for Generalizable Speech Separation}, author={Joris Cosentino and Manuel Pariente and Samuele Cornell and Antoine Deleforge and Emmanuel Vincent}, year={2020}, eprint={2005.11262}, archivePrefix={arXiv}, primaryClass={eess.AS} } N)ThreadPoolExecutor as_completed)Path)DictListOptionalTuple) AudioSource Recording RecordingSet)info save_audio)CutSetMonoCutmix)manifests_existread_manifests_if_cached)Pathlikei>cCsNtjj|ddid}tj| }t|WdS1s wYdSNz User-Agentz python-urllib)headers)urllibrequestRequesturlopenjsonloadurlreqrespr K/home/ubuntu/.local/lib/python3.10/site-packages/lhotse/recipes/librimix.py _fetch_jsonPs$r"cCsLtjj|ddid}tj| }|WdS1swYdSr)rrrrreadrr r r! _fetch_bytesVs$r$main.c Csd|d|d|d|}t|}tj|dd|D]@}tj||d}|dd krKt|d } | t|d Wdn1sEwYq|dd kr[t|||d ||qdS)Nzhttps://api.github.com/repos//z /contents/z?ref=Texist_oknametypefilewb download_urldirpath) r"osmakedirsr0joinopenwriter$download_github_dir) userrepor0branchsave_dirapi_urlfilesr, file_pathfr r r!r6\s   r6 target_dirreturncCst|}|jddd|d}|d}|r"td|d|Std|dtj|dd td d dd |||S) zDownload LibriMix metadata.Tparentsr)metadata .completedzSkipping download because z exists.zIDownloading https://github.com/JorisCos/LibriMix/tree/master/metadata to ...r(JorisCosLibriMixmaster) rmkdiris_fileloggingr r1r2r6touch)r? metadata_dircompleted_detectorr r r!download_librimixks rOlibrispeech_root_pathwham_recset_root_pathlibrimix_metadata_pathworkdir output_dirn_srcnum_jobsc Cstd|durt|}|jddd|dur#t|}|jdddi}g}t|d|d} ddt| D} | D]} | d d d } | d d d } || | gq=|duret||d dd}t |}t|d|d} ddt| D} | D]o} | d d } | d d d } t | |d ddrt | |d ddrt d| d| dqt | | |||||\}}t |}|dur||d| dd|i|| <t |}|dur||d| dd|i|| <q|S)aJ Prepare LibriMix manifests for multi-speaker mixtures. Args: librispeech_root_path: Path to LibriSpeech manifests wham_recset_root_path: Path to WHAM noise manifests librimix_metadata_path: Path to LibriMix metadata output_dir: Directory to save manifests workdir: Working directory for temporary files n_src: Number of sources to for mixing num_jobs: Number of parallel threads used for processing (default: 1) Returns: Dict with keys for each split containing 'cuts' for both clean and noisy versions a>The original LibriMix recipe introduces a quantization error when saving audio files via soundfile, which by default uses PCM_16 format. If you need to replicate the exact quantization behavior from the original recipe, you can save and load the audio using a temporary file as shown in the docstring of this function.NTrALibriMixcS g|] }d|vr|dkr|qSr rDr .0r,r r r! z$prepare_librimix...csv_clean_noisylibrimix)cutset) dataset_partsrVprefixtypescSr[r\r r]r r r!r_r`)partrVrhrizLibriMix subset: z and z already prepared - skipping.librimix_cutset_ .jsonl.gzrf)rKwarningrrIr1listdirreplaceextendr_load_wham_recordingsrr _process_metadata_filer from_cutsto_file)rRrSrTrUrVrWrX manifestsrgn_src_meta_rootmd_filename_list md_filename part_namepart_name_noisy wham_recsets clean_cuts noisy_cuts clean_cutset noisy_cutsetr r r!prepare_librimixs   rcs8gd}gd}fdd|D}t|d||d<|S)z>Load WHAM recordings with speed augmentation for training set.))trainzwham_recordings_tr.jsonl.gz)devzwham_recordings_cv.jsonl.gz)testzwham_recordings_tt.jsonl.gz)g??g333333?cs$i|]\}}|tt|qSr )lhotse load_manifestr)r^keysplitrSr r! sz)_load_wham_recordings..r) _augment_wham)rS wham_splits speed_factorsr{r rr!rqs rqrecsetrcsbddldtdtffdd }g}|D]}|dkr||}n|}||}||qt|S)z,Apply speed augmentation to WHAM recordings.rN recordingr@csdd|j|_|S)Nz_sp(\d+)\.(\d+)$zsp\1\2)subid)rrer r! fix_rec_idssz"_augment_wham..fix_rec_idsr)rr perturb_speedmaprpr from_recordings)rrr new_recset speed_factoraugmented_recsetr rr!r s    rnoise max_lengthc Cs|}ttd}|dt|dd}|t|ddd}t||kr^t|dt|t|t|t|t|d|t|dt|||t|df}t||ks&|d|S)z'Concatenate noise using Hanning window.rQNrP)nphanningRATElen concatenatemultiply)rrnoise_exwindowi_wd_wr r r! _extend_noise s  rrowlibrispeech_cutset wham_recsetcCsg}g}td|dD]}|t|d|dj||d|dq |j|d}ddt||D}|} |rFt| |} |s=|d| _t|d j} || } |d } | | } | j | j krnt | | |d|} t d d | j d | d }t| |dd}| |fS)z'Process a single row from metadata CSV.rQsource__path_gain)cut_idscSsg|] \}}||qSr )perturb_volume)r^srcgainr r r!r_Csz _process_row.. mixture_ID noise_path noise_gainrr)rstartdurationchannelrleft) preserve_id) rangeappendrstemsubsetzippoprrrr_extend_noise_recordingr)rrrrWrUsrcsgainsrnormalized_cuts clean_mixnoise_id noise_recrnoise_rec_perturbed noise_cut noisy_mixr r r! _process_row3s:      rrr mixture_idc Cs|durtd}||jd|d}|s7|}|jdkr$|d}t|t|j|j}t |||jdt |}t ddgt |d }t |j|g|j|j|jd S) z3Extend noise recording to match clean mix duration.Nr&_z.wavrQr)destr sampling_rater,)r+channelssource)rsourcesr num_samplesr)rrexists load_audiondimrintrrr r r strr samplerateframes) rrrrUsave_to noise_arrayextended_noisenoise_rec_info new_sourcer r r!rbs, rcsv_pathcCsg}t|ddd.}t|}|D]}t|D]\}}|dr(t|||<q||qWd|S1s:wY|S)zc Read LibriMix metadata using Python's standard csv library and cast gain fields to float. rrb)newlinerN)r4csv DictReaderlistitemsendswithfloatr)rrowsr>readerrkvr r r!_read_metadata_csvs     rrxrvr{cs||}t|}tt||dddddddd|d d d d d } || g} g} t d|dt |d6fdd|D} t j t | t | dD]} | \}}| || |qdWd | | fS1swY| | fS)z?Process a single metadata file and return clean and noisy cuts.librirrrarlcSsd|dddS)N-r)r3r)cr r r!sz(_process_metadata_file..rbrrQNrrz Processing rE) max_workersc s g|] }t|qSr )submitr)r^rexrrWrrUr r!r_s  z*_process_metadata_file..)total)rrrrro modify_idsr3rrKr rtqdmrrresultr)rxrvrWrRr{rUrXrr split_namer|r}futuresr>rrr rr!rrs< "       rr)r%r&)r&)NrPrQ)7__doc__rrrKr1urllib.requestrconcurrent.futuresrrpathlibrtypingrrrrnumpyrrr lhotse.audior r r lhotse.audio.backendr r lhotse.cut.setrrrlhotse.recipes.utilsrr lhotse.utilsrrr"r$r6rOrrrrqrrndarrayrdictrrrrrr r r r!s9     { /