Metadata-Version: 2.1
Name: pydrobert-kaldi
Version: 0.6.1
Summary: Python wrapper for Kaldi
Home-page: https://github.com/sdrobert/pydrobert-kaldi
Author: Sean Robertson
Author-email: sdrobert@cs.toronto.edu
License: Apache-2.0
Project-URL: Documentation, https://pydrobert-kaldi.readthedocs.io
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: pytorch
License-File: LICENSE

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# pydrobert-kaldi

Some [Kaldi](http://kaldi-asr.org/) bindings for Python. I started this project
because I wanted to seamlessly incorporate [Kaldi's I/O
mechanism](http://kaldi-asr.org/doc/io.html) into the gamut of Python-based
data science packages (e.g. Theano, Tensorflow, CNTK, PyTorch, etc.). The code
base is expanding to wrap more of Kaldi's feature processing and mathematical
functions, but is unlikely to include modelling or decoding.

Eventually, I plan on adding hooks for Kaldi audio features and pre-/post-
processing. However, I have no plans on porting any code involving modelling or
decoding.

**This is student-driven code, so don't expect a stable API. I'll try to use
semantic versioning, but the best way to keep functionality stable is by
forking.**

## Documentation

- [Latest](https://pydrobert-kaldi.readthedocs.io/en/latest/)

## Input/Output

Most I/O can be performed with the `pydrobert.kaldi.io.open` function:


``` python
from pydrobert.kaldi import io
with io.open('scp:foo.scp', 'bm') as f:
     for matrix in f:
         ...
```

`open` is a factory function that determines the appropriate underlying stream
to open, much like Python's built-in `open`. The data types we can read (here,
a `BaseMatrix`) are listed in `pydrobert.kaldi.io.enums.KaldiDataType`. Big
data types, like matrices and vectors, are piped into Numpy arrays. Passing an
extended filename  (e.g. paths to files on discs, `'-'` for stdin/stdout,
`'gzip -c a.ark.gz |'`, etc.) opens a stream from which data types can be read
one-by-one and in the order they were written. Alternatively, prepending the
extended filename with `'ark[,[option_a[,option_b...]]:'` or `'scp[,...]:'` and
specifying a data type allows one to open a Kaldi table for iterator-like
sequential reading (`mode='r'`), dict-like random access reading (`mode='r+'`),
or writing (`mode='w'`). For more information on the open function, consult the
docstring.

The submodule `pydrobert.kaldi.io.corpus` contains useful wrappers around Kaldi
I/O to serve up batches of data to, say, a neural network:

``` python
train = ShuffledData('scp:feats.scp', 'scp:labels.scp', batch_size=10)
for feat_batch, label_batch in train:
    ...
```

## Logging and CLI

By default, Kaldi error, warning, and critical messages are piped to standard
error. The `pydrobert.kaldi.logging` submodule provides hooks into python's
native logging interface: the `logging` module. The :class:`KaldiLogger` can
handle stack traces from Kaldi C++ code, and there are a variety of decorators
to finagle the kaldi logging patterns to python logging patterns, or vice
versa.

You'd likely want to explicitly handle logging when creating new kaldi-style
commands for command line. `pydrobert.kaldi.io.argparse` provides
:class:`KaldiParser`, an :class:`ArgumentParser` tailored to Kaldi
inputs/outputs. It is used by a few command-line entry points added by this
package. See the [Command-Line
Interface](http://pydrobert-kaldi.readthedocs.io/en/latest/cli.html) page for
details.

## Installation

Prepackaged binaries of tagged versions of `pydrobert-kaldi` are available for
most platforms (64-bit Windows, 32/64-bit Glibc Linux, OSX) and most active
Python versions (3.7-3.10).

To install via [conda](https://docs.conda.io/en/latest/)

``` sh
   conda install -c sdrobert pydrobert-kaldi
```

A [conda-forge](https://conda-forge.org/) version is TBD.

To install via [PyPI](https://pypi.org/)

``` sh
   pip install pydrobert-kaldi
```

You can also try building the cutting-edge version. To do so, you'll need to
first install [SWIG 4.0](https://www.swig.org/) and an appropriate C++
compiler, then

``` sh
   pip install git+https://github.com/sdrobert/pydrobert-kaldi.git
```

The current version does not require a BLAS install, though it likely will in
the future as more is wrapped.

## License

This code is licensed under Apache 2.0.

Code found under the `src/` directory has been primarily copied from Kaldi.
`setup.py` is also strongly influenced by Kaldi's build configuration. Kaldi is
also covered by the Apache 2.0 license; its specific license file was copied
into `src/COPYING_Kaldi_Project` to live among its fellows.

## How to Cite

Please see the [pydrobert page](https://github.com/sdrobert/pydrobert) for more
details.
