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  • Conformer: Convolution-augmented Transformer for Speech Recognition
    To this regard, we propose the convolution-augmented transformer for speech recognition, named Conformer Conformer significantly outperforms the previous Transformer and CNN based models achieving state-of-the-art accuracies
  • GitHub - sooftware conformer: [Unofficial] PyTorch implementation of . . .
    Conformer combine convolution neural networks and transformers to model both local and global dependencies of an audio sequence in a parameter-efficient way Conformer significantly outperforms the previous Transformer and CNN based models achieving state-of-the-art accuracies
  • Conformer（cnn+transformers）论文详解 - CSDN博客
    在本文中，我们提出了一种称为 Conformer 的混合网络结构，以利用卷积运算和自注意力机制来增强表示学习。 Conformer 源于特征耦合单元 (FCU)，它以交互方式融合不同分辨率下的局部特征和全局表示。 Conformer 采用并发结构，最大限度保留局部特征和全局表征。
  • Conformer: Convolution-augmented Transformer for Speech . . . - DeepAI
    To this regard, we propose the convolution-augmented transformer for speech recognition, named Conformer Conformer significantly outperforms the previous Transformer and CNN based models achieving state-of-the-art accuracies On the widely used LibriSpeech benchmark, our model achieves WER of 2 1 using a language model and 1 9 test testother
  • Conformer论文以及代码解析（上） - CSDN博客
    Conformer论文提出了结合卷积和Transformer优点的网络结构，通过Feature Coupling Unit(FCU)融合局部与全局特征，解决了卷积网络捕捉全局特征不足和Transformer忽视局部特征的问题。
  • Conformer: Convolution-augmented Transformer for Speech Recognition . . .
    Conformer significantly outperforms the previous Transformer and CNN based models achieving state-of-the-art accuracies On the widely used LibriSpeech benchmark, our model achieves WER of 2 1% 4 3% without using a language model and 1 9% 3 9% with an external language model on test testother
  • Conformer: Convolution-augmented Transformer for Speech Recognition
    We propose the convolution-augmented transformer for speech recognition, named \textit{Conformer} \textit{Conformer} achieves state-of-the-art accuracies while being parameter-efficient, outperforming all previous models in ASR
  • Conformer模型模型 Conformer（Convolution-augmented Transformer）是一 - 掘金
    Conformer（Convolution-augmented Transformer）是一种结合了卷积神经网络（CNN）和Transformer的深度学习模型，旨在提升语音识别等任务的性能。 它的设计目标是结合卷积层的局部特征提取能力和Transformer的长程依赖建模能力，从而有效地处理时序数据，尤其适用于语音和
  • Conformer:用于语音识别的卷积增强Transformer - CSDN博客
    论文： Conformer: Convolution-augmented Transformer for Speech Recognition 摘要： 讲了基于CNN和Transformer的语音识别模型表现比以RNN为基础的模型好，Transformer模型擅长捕获基于内容的全局交互，而CNN则有效地利用了局部特征。
  • Conformer: 卷积增强的Transformer - 知乎 - 知乎专栏
    参考文献[1]中提出的conformer是用卷积去加强Transformer在语音识别领域的效果。 而参考文献[2]则是用 注意力机制 去增强卷积网络的效果。 下面，我们先来看一下conformer是如何做的。





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