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mlp

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OpenCL for Nets - A Deep Learning Framework based on OpenCL, written by C++. Supports popular MLP, RNN(LSTM), CNN(ResNet). Friendly debugger. Transparent data. No library dependencies. 基于OpenCL的深度学习计算框架,C++开发,支持多层感知器,长短时记忆模型,卷积神经网络,残差网络。调试方便,数据透明。无外部依赖。

  • Updated Jun 3, 2019
  • C

Speaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).

  • Updated Jul 31, 2020
  • Python

This code implements a basic MLP for speech recognition. The MLP is trained with pytorch, while feature extraction, alignments, and decoding are performed with Kaldi. The current implementation supports dropout and batch normalization. An example for phoneme recognition using the standard TIMIT dataset is provided.

  • Updated Feb 10, 2018
  • Perl
ClashLuke
ClashLuke commented Nov 24, 2019

Hello there,
I recently stumbled upon this repository and was interested in trying out your code. However, using single-threaded sklearn doesn't seem to be efficient to me, compared to using GPU-optimized PyTorch or TF.
Do you have any plans of moving to those frameworks, or would you accept a pullrequest implementing these?
Regards,
Luke

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