Refactor prep_segments in SVS #5210
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jerryuhoo
changed the title
| label_info, text_info = process_text_info( | ||
| os.path.join(src_data, folder, "{}.lab".format(folder)) | ||
| ) | ||
| # text_scp.write("{} {}\n".format(utt_id, text_info)) |
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Why do you remove the write of text_scp and midiscp?
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Why do you remove the write of text_scp and midiscp?
I think they are not used in this dataset. I find that ofuton also doesn't use text_scp and midiscp, so I removed them. Should I keep them?
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If it is not used, let's remove them.
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The modification functions in new prep_segment look great. But it would be too long if we put all datasets in it. |
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I see. I think it would be a good idea to generate a dict in check_align.py, then I can use the dict in prep_segments.py. In that case, all the errors will be auto-fixed, and we don't have to put those dicts inside the code. But currently I don't know how to save and load (also append a function to) this dict. |
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Looks good to me. Could you also add the related docs in template/svs1/readme ? I'm still not pretty sure about the potential steps we need to do with the regarding updates. |
| label_info, text_info = process_text_info( | ||
| os.path.join(src_data, folder, "{}.lab".format(folder)) | ||
| ) | ||
| # text_scp.write("{} {}\n".format(utt_id, text_info)) |
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If it is not used, let's remove them.
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LGTM! @A-Quarter-Mile could you double check it? |
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I still suggest removing natsume from new prep_segments and keeping the one in local/. There are some special designs for it (mid_reader and align_lyric_notes), which are not applicable for other datasets. Besides, the modifications for natsume in new prep_segments are based on manual inspection, we can remove them safely. |
Co-authored-by: Jiatong <728307998@qq.com>
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LGTM! @A-Quarter-Mile could you double check this update? After your confirmation and CI cleared, I will merge the PR. |
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Many thanks! Code merged. |
@ftshijt @A-Quarter-Mile
I plan to use only one file for preprocessing labels and XML files, instead of using
local/prep_segments.pyandlocal/prep_segments_from_xml.pyin every dataset, which will be placed underpyscripts/utils.To fix dataset errors, we can use several functions (
replace_lyrics,replace_labels,skip_labels,add_missing_phoneme,add_pause) to handle specific errors. We can use a dictionaryerror_correctionto store error handling functions in each dataset.In order to use this new function, previous scripts for datasets that use XML files should be changed.
pyscripts/utils/prep_segments.pyand add parameters such as--dataset natsumeand--input_type hts/xml. Please see Natsume example.local/prep_segments.py,local/prep_segments_from_xml.pyandpyscripts/utils/prep_segments_from_xml.py