Attention mechanisms are at the core of transformer architectures, enabling models to capture relationships within and across sequences. Two critical attention types are Self-Attention and ...

Modern systems for automatic speech recognition, including the RNN-Transducer and Attention-based Encoder-Decoder (AED), are designed so that the encoder is not required to alter the time-position of ...

This encoder-decoder model is trained for language translation. I chose to keep things somewhat simple for this project and utilize a word-level tokenizer from HuggingFace instead of a more ...

In this work, we propose the first method to explain prediction by any Transformer-based architecture, including bi-modal Transformers and Transformers with co-attentions. We provide generic solutions ...

Standard transformer architecture consists of three main components - the encoder, the decoder and the attention mechanism. The encoder processes input data to generate a series of tokens, while ...

Facial Emotion Recognition (FER) has emerged as an essential task in affective computing, with a wide range of utilization from man-machine interaction to health monitoring. A novel technique of FER ...