======== nara_wpe
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Weighted Prediction Error for speech dereverberation
Background noise and signal reverberation due to reflections in an enclosure are the two main impairments in acoustic signal processing and far-field speech recognition. This work addresses signal dereverberation techniques based on WPE for speech recognition and other far-field applications. WPE is a compelling algorithm to blindly dereverberate acoustic signals based on long-term linear prediction.
The main algorithm is based on the following paper: Yoshioka, Takuya, and Tomohiro Nakatani. "Generalization of multi-channel linear prediction methods for blind MIMO impulse response shortening." IEEE Transactions on Audio, Speech, and Language Processing 20.10 (2012): 2707-2720.
Content
- Iterative offline WPE/ block-online WPE/ recursive frame-online WPE
- All algorithms implemented both in Numpy and in TensorFlow (works with version
1.12.0). - Continuously tested with Python 3.7, 3.8, 3.9 and 3.10.
- Automatically built documentation:
nara-wpe.readthedocs.io <https://nara-wpe.readthedocs.io/en/latest/>_ - Modular design to facilitate changes for further research
Installation
Install it directly with Pip, if you just want to use it:
.. code-block:: bash
pip install nara_wpe
If you want to make changes or want the most recent version: Clone the repository and install it as follows:
.. code-block:: bash