Change log¶
v0.1.0 <2021-08-11>¶
#114: Use pysen for linting/formatting
Removed display package
Fix hts.load when the input label is empty
Add hts.io.HTSLabelFile.create_from_contexts
Fix build time numpy requirement to <v1.20.0
Support for loading HTS-style labels with time unit in seconds
v0.0.23 <2021-05-15>¶
#112: Renamed continuous_dict to numeric_dict to be more precise.
#112: Bandmat is now a part of nnmnkwii’s internal package. This is to avoid instllation failusres on python >=3.6. https://github.com/MattShannon/bandmat/issues/10
#112: Started testing using github actions (python 3.7, 3.8, 3.9)
#112: [hts.io]:
nnmnkwii.io.hts.load_question_set()
now keeps question names (e.g. “L-Phone_Boin”) in dictionary.#112: [hts.io]: New functionality
nnmnkwii.io.hts.write_audacity_labels()
#112: [hts.io]: New functionality
nnmnkwii.io.hts.write_textgrid()
#112: Renamed np.int to int
#112: Added pyproject.yaml
v0.0.22 <2020-12-25>¶
v0.0.21 <2020-08-13>¶
v0.0.20 <2020-03-02>¶
v0.0.19 <2019-07-06>¶
#88: Tentative fix: make bandmat optional requirement as it is causing installation errors on python 3.7. See [here](https://github.com/MattShannon/bandmat/issues/10) for details.
#85: Fixed rounding error in caluculating number of frames.
#87: Fixed
nnmnkwii.preprocessing.trim_zeros_frames()
issue. Support passingtrim
argument.
v0.0.18 <2019-05-31>¶
Fix for python 3.7.
v0.0.17 <2018-12-25>¶
v0.0.16 <2018-08-23>¶
v0.0.15 <2018-07-12>¶
Fix pypi release to render markdown property
v0.0.14 <2018-06-06>¶
v0.0.13 <2018-01-24>¶
v0.0.12 <2018-01-04>¶
Fix typo:
adjast_frame_length
andadjast_frame_lengths
are renamed toadjust_frame_length
andadjust_frame_lengths
, respectively,#63: Improved support for
nnmnkwii.preprocessing.adjast_frame_length()
andnnmnkwii.preprocessing.adjast_frame_lengths()
. Padding for 1d array is now supported.BUG FIX: example audio data is now included in the release tar.gz
v0.0.11 <2017-12-22>¶
Fix RuntimeError when HTS label file has white spaces between fields. Skip comments when reading HTS labels.
v0.0.10 <2017-12-05>¶
#61: Misc dataset improvements. Unified max_files=None from max_files=50 and add max_files args for VCTK data sources.
#59: Bug fix for memory re-allocations when num frames exceed padded_initial_guess
#60: FileSourceDataset: better descriptive error messages
#57: Add
append
method to HTSLabelFile and simplify structure.frame_shift_in_micro_sec
was removed from its property.#55: Add mu-law companding/expansion
Add support for JSUT dataset ver 1.1
#20: Support for mono phone labels and fix bug of
silence_phone_indices()
for non-state level alignment label files.
v0.0.9 <2017-11-14>¶
v0.0.8 <2017-10-25>¶
v0.0.7 <2017-10-09>¶
#12: [experimental] Add
nnmnkwii.metrics
package#42: Fix installation failsure on no-utf-8 environments
v0.0.6 <2017-10-01>¶
#38: Add parameter trajectory smoothing.
#37: Add
tqdm
as dependency. Dataset’sasarray
now report progress ifverbose > 0
.#37: Add further support for incremental mean/var computation.
#37: Add and improve normalization utilities,
nnmnkwii.preprocessing.inv_scale()
,nnmnkwii.preprocessing.inv_minmax_scale()
andnnmnkwii.preprocessing.minmax_scale_params()
.Add builtin data source for Voice Conversion Challenge (VCC) 2016 dataset.
#34: Add
nnmnkwii.preprocessing.adjast_frame_length()
.#34:
adjast_frame_lengths
now supportsdivisible_by
parameter.ensure_even
is deprecated.#34: Rename
adjast_frame_length
toadjast_Frame_lengths
Add references to
nnmnkwii.postfilters.merlin_post_filter()
.
v0.0.5 <2017-09-19>¶
#19: Achieved 80% test coverage
#31: Cleanup data source implementations and add docs.
Fix example data wasn’t included in release tar ball.
Support
padded_length
isNone
fornnmnkwii.datasets.FileSourceDataset
.Automatic frame length adjastment for DTWAligner / IterativeDTWAligner
v0.0.4 <2017-09-01>¶
v0.0.3 <2017-08-26>¶
Add tests, achieve 75% test coverage.
#21: Add new function
nnmnkwii.autograd.UnitVarianceMLPG
that can run on CPU/GPU.
v0.0.2 <2017-08-18>¶
hts io: Add support for full-context only label files
#17: ts io: Fix wildcard handling bug
Use pack_pad_sequence for RNN training and add tests for this
Faster MLPG gradient computation
v0.0.1 <2017-08-14>¶
Initial release