May 16, 2020 · To this regard, we propose the convolution-augmented transformer for speech recognition, named Conformer. Conformer significantly outperforms the previous Transformer and …

Conformer roots in the Feature Coupling Unit (FCU), which fuses local features and global representations under different resolutions in an interactive fashion. Conformer adopts a concurrent …

Jul 19, 2023 · We're introducing Conformer-2, our latest AI model for automatic speech recognition. Conformer-2 is trained on 1.1M hours of English audio data, extending Conformer-1 to provide …

Jun 10, 2024 · A conformer block is composed of four modules stacked together, i.e, a feed-forward module, a self-attention module, a convolution module, and a second feed-forward module in the end.

Nov 13, 2025 · This blog post aims to provide a detailed guide on Conformer in PyTorch, covering its fundamental concepts, usage methods, common practices, and best practices.

Conformer architecture introduced in Conformer: Convolution-augmented Transformer for Speech Recognition [Gulati et al., 2020]. input_dim (int) – input dimension. num_heads (int) – number of …

Nov 13, 2020 · In this paper, we call this combination of transformer and CNNs as Conformer. And, not surprisingly, this Conformer has significantly outperformed previous studies. In recent years, the …

In this work, we study how to combine convolutions and transformers to model both global interactions and the local patterns of an audio sequence in a parameter-efficient way.

May 16, 2020 · Conformer stands for “Convolution-augmented Transformer” which is an encoder architecture that combines convolution neural networks (CNN) and Transformers to perform speech …

Conformer Implementation of the convolutional module from the Conformer paper, for improving the local inductive bias in Transformers.