Mixed Precision Low-bit Quantization of Neural Network Language Models for Speech Recognition
Junhao Xu,
Jianwei Yu,
Shoukang Hu
et al.
Abstract:State-of-the-art language models (LMs) represented by long-short term memory recurrent neural networks (LSTM-RNNs) and Transformers are becoming increasingly complex and expensive for practical applications. Low-bit neural network quantization provides a powerful solution to dramatically reduce their model size. Current quantization methods are based on uniform precision and fail to account for the varying performance sensitivity at different parts of LMs to quantization errors. To this end, novel mixed precis… Show more
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