o Siu,@sdZddlZddlZddlZddlZddlmZddlmZddl m Z m Z m Z ddl mZmZmZmZmZddlmZddlmZmZd Zd Zd d d efd ede ede ede edef ddZ  ddede ede ede ede ee eefff ddZdedefddZdS)a This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent archive. The newspaper texts were taken from Herald Glasgow, with permission from Herald & Times Group. Each speaker has a different set of the newspaper texts selected based a greedy algorithm that increases the contextual and phonetic coverage. The details of the text selection algorithms are described in the following paper: C. Veaux, J. Yamagishi and S. King, "The voice bank corpus: Design, collection and data analysis of a large regional accent speech database," https://doi.org/10.1109/ICSDA.2013.6709856 The rainbow passage and elicitation paragraph are the same for all speakers. The rainbow passage can be found at International Dialects of English Archive: (http://web.ku.edu/~idea/readings/rainbow.htm). The elicitation paragraph is identical to the one used for the speech accent archive (http://accent.gmu.edu). The details of the the speech accent archive can be found at http://www.ualberta.ca/~aacl2009/PDFs/WeinbergerKunath2009AACL.pdf All speech data was recorded using an identical recording setup: an omni-directional microphone (DPA 4035) and a small diaphragm condenser microphone with very wide bandwidth (Sennheiser MKH 800), 96kHz sampling frequency at 24 bits and in a hemi-anechoic chamber of the University of Edinburgh. (However, two speakers, p280 and p315 had technical issues of the audio recordings using MKH 800). All recordings were converted into 16 bits, were downsampled to 48 kHz, and were manually end-pointed. This corpus was originally aimed for HMM-based text-to-speech synthesis systems, especially for speaker-adaptive HMM-based speech synthesis that uses average voice models trained on multiple speakers and speaker adaptation technologies. This corpus is also suitable for DNN-based multi-speaker text-to-speech synthesis systems and waveform modeling. COPYING This corpus is licensed under the Creative Commons License: Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/legalcode VCTK VARIANTS There are several variants of the VCTK corpus: Speech enhancement - Noisy speech database for training speech enhancement algorithms and TTS models where we added various types of noises to VCTK artificially: http://dx.doi.org/10.7488/ds/2117 - Reverberant speech database for training speech dereverberation algorithms and TTS models where we added various types of reverberantion to VCTK artificially http://dx.doi.org/10.7488/ds/1425 - Noisy reverberant speech database for training speech enhancement algorithms and TTS models http://dx.doi.org/10.7488/ds/2139 - Device Recorded VCTK where speech signals of the VCTK corpus were played back and re-recorded in office environments using relatively inexpensive consumer devices http://dx.doi.org/10.7488/ds/2316 - The Microsoft Scalable Noisy Speech Dataset (MS-SNSD) https://github.com/microsoft/MS-SNSD ASV and anti-spoofing - Spoofing and Anti-Spoofing (SAS) corpus, which is a collection of synthetic speech signals produced by nine techniques, two of which are speech synthesis, and seven are voice conversion. All of them were built using the VCTK corpus. http://dx.doi.org/10.7488/ds/252 - Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015) Database. This database consists of synthetic speech signals produced by ten techniques and this has been used in the first Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2015) http://dx.doi.org/10.7488/ds/298 - ASVspoof 2019: The 3rd Automatic Speaker Verification Spoofing and Countermeasures Challenge database. This database has been used in the 3rd Automatic Speaker Verification Spoofing and Countermeasures Challenge (ASVspoof 2019) https://doi.org/10.7488/ds/2555 ACKNOWLEDGEMENTS The CSTR VCTK Corpus was constructed by: Christophe Veaux (University of Edinburgh) Junichi Yamagishi (University of Edinburgh) Kirsten MacDonald The research leading to these results was partly funded from EPSRC grants EP/I031022/1 (NST) and EP/J002526/1 (CAF), from the RSE-NSFC grant (61111130120), and from the JST CREST (uDialogue). Please cite this corpus as follows: Christophe Veaux, Junichi Yamagishi, Kirsten MacDonald, "CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit", The Centre for Speech Technology Research (CSTR), University of Edinburgh N) defaultdict)Path)DictOptionalUnion) Recording RecordingSetSupervisionSegmentSupervisionSet$validate_recordings_and_supervisions) fix_manifests)Pathlikeresumable_downloadzKhttps://datashare.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zipz4http://www.udialogue.org/download/VCTK-Corpus.tar.gz.F target_dirforce_downloaduse_edinburgh_vctk_urlurlreturnc Cst|}|jddd|rt}|dd}||}||dddd}|d}|r  zprepare_vctk..z*.flacwav48csr<r=r>)r@wavr4r4r5rBrCz*.wavtxtz*.txt_rp280r7p362cSsdSr=r4r4r4r4r5szprepare_vctk..Nz!Cannot find metadata for speaker rEnglishgenderaccentageregion)rMrNrO) id recording_idstartdurationtextlanguagespeakerrLcustomTrzvctk_recordings_all.jsonl.gzzvctk_supervisions_all.jsonl.gz) recordings supervisions)ris_dir_parse_speaker_descriptionrfrom_recordingsrglob read_textstripnamer stemsourcessourcer"getrr#warningappendr rSr from_segmentsr r rto_file)r8r9rr: speaker_meta audios_dirrXrYrrTrVseg_id audio_file_idaudio_file_pathmetar4r4r5 prepare_vctksv         roc Csi}dd|dD}|d}tgdt|s J|ddD]#^}}}}} t|||| dur;d| ndd||sFd |n|<q&|S) NcSsg|]}|qSr4)r )r@liner4r4r5 sz._parse_speaker_description..zspeaker-info.txtr)IDAGEGENDERACCENTSREGION )rNrLrMrOp)r^ splitlinessetissubsetintjoin) r8rrnlinesheaderspkrNrLrMrOr4r4r5r[sr[)NFr7)__doc__r#r%r*r( collectionsrpathlibrtypingrrrlhotserrr r r lhotse.qar lhotse.utilsr rrCREST_VCTK_URLboolstrr6ror[r4r4r4r5sXO    * b