Metadata-Version: 2.1
Name: kaldi-active-grammar
Version: 0.3.0
Summary: Kaldi speech recognition with grammars that can be set active/inactive dynamically at decode-time
Home-page: https://github.com/daanzu/kaldi-active-grammar
Author: David Zurow
Author-email: daanzu@gmail.com
License: AGPL-3.0, with exceptions
Keywords: kaldi speech recognition grammar
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Requires-Python: >=2.7, <3
Description-Content-Type: text/markdown
Requires-Dist: cffi
Requires-Dist: numpy
Requires-Dist: six

# Kaldi Active Grammar

> **Python Kaldi speech recognition with grammars that can be set active/inactive dynamically at decode-time**

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> Python package developed to enable context-based command & control of computer applications, as in the [Dragonfly](https://github.com/dictation-toolbox/dragonfly) speech recognition framework, using the [Kaldi](https://github.com/kaldi-asr/kaldi) automatic speech recognition engine.

> **_BETA RELEASE_**

Normally, Kaldi decoding graphs are **monolithic**, require **expensive up-front off-line** compilation, and are **static during decoding**. Kaldi's new grammar framework allows **multiple independent** grammars with nonterminals, to be compiled separately and **stitched together dynamically** at decode-time, but all the grammars are **always active** and capable of being recognized.

This project extends that to allow each grammar/rule to be **independently marked** as active/inactive **dynamically** on a **per-utterance** basis (set at the beginning of each utterance). Dragonfly is then capable of activating **only the appropriate grammars for the current environment**, resulting in increased accuracy due to fewer possible recognitions. Furthermore, the dictation grammar can be **shared** between all the command grammars, which can be **compiled quickly** without needing to include large-vocabulary dictation directly.

* The Python package **includes all necessary binaries** for decoding on **Linux or Windows**.
* A compatible [**general English Kaldi nnet3 chain model**](https://github.com/daanzu/kaldi-active-grammar/releases/latest/download/kaldi_model_zamia.zip) is available, under releases.
* A compatible [**backend for Dragonfly**](https://github.com/daanzu/dragonfly/tree/kaldi/dragonfly/engines/backend_kaldi) is under development, currently in the kaldi branch of my fork.

Donations are appreciated to encourage development.

## Setup

Requirements:
* Python 2.7 (3.x support planned); *64-bit required!*
    * Microphone support provided by [pyaudio](https://pypi.org/project/PyAudio/) package
* OS: *Linux or Windows*; macOS planned if there is interest
* Only supports Kaldi left-biphone models, specifically *nnet3 chain* models

Install Python package, which includes necessary Kaldi binaries:

```
pip install kaldi-active-grammar
```

Download compatible generic English Kaldi nnet3 chain model from project releases. Unzip the model and pass the directory path to kaldi-active-grammar constructor.

Or use your own model. Standard Kaldi models must be converted to be usable. Conversion can be performed automatically, but this hasn't been fully implemented yet.

### Troubleshooting

* Errors installing
    * Make sure you are using a 64-bit Python.
    * Update your `pip` by executing `pip install --upgrade pip`.

## Contributing

Please feel free to submit issues, suggestions, and feature requests. Pull requests are considered, but project structure is in flux.

Donations are appreciated to encourage development.

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## Author

* David Zurow ([@daanzu](https://github.com/daanzu))

## License

This project is licensed under the GNU Affero General Public License v3 (AGPL-3.0), with the exception of the associated binaries, whose source is currently unreleased and which are only to be used by this project. See the LICENSE.txt file for details.

If this license is problematic for you, please contact me.

## Acknowledgments

* Based on and including code from [Kaldi ASR](https://github.com/kaldi-asr/kaldi), under the Apache-2.0 license.
* Code from [OpenFST](http://www.openfst.org/) and [OpenFST port for Windows](https://github.com/kkm000/openfst), under the Apache-2.0 license.
* [Intel Math Kernel Library](https://software.intel.com/en-us/mkl), copyright (c) 2018 Intel Corporation, under the [Intel Simplified Software License](https://software.intel.com/en-us/license/intel-simplified-software-license).
* Modified generic English Kaldi nnet3 chain model from [Zamia Speech](https://github.com/gooofy/zamia-speech), under the LGPL-3.0 license.


