论文标题
基于神经网络的语音识别的适应算法：概述
Adaptation Algorithms for Neural Network-Based Speech Recognition: An Overview
论文作者
论文摘要
我们介绍了基于神经网络的语音识别的适应算法的结构化概述，考虑了混合隐藏的马尔可夫模型 /神经网络系统和端到端的神经网络系统，重点关注说话者的适应性，域的适应性和重音适应。概述将适应算法表征为基于嵌入，模型参数适应或数据增强。我们基于文献中报告的相对错误率降低，对语音识别适应算法的性能进行了荟萃分析。
We present a structured overview of adaptation algorithms for neural network-based speech recognition, considering both hybrid hidden Markov model / neural network systems and end-to-end neural network systems, with a focus on speaker adaptation, domain adaptation, and accent adaptation. The overview characterizes adaptation algorithms as based on embeddings, model parameter adaptation, or data augmentation. We present a meta-analysis of the performance of speech recognition adaptation algorithms, based on relative error rate reductions as reported in the literature.
