Recently, sequential transfer learning emerged as a modern technique for applying the
“pretrain then fine-tune” paradigm to leverage existing knowledge to improve the …

Sentiment analysis is a computational technique that analyses the subjective information
conveyed within a given expression. This encompasses appraisals, opinions, attitudes or …

The wide application of smart devices enables the availability of multimodal data, which can
be utilized in many tasks. In the field of multimodal sentiment analysis, most previous works …

Radiology report generation (RRG) aims to describe automatically a radiology image with
human-like language and could potentially support the work of radiologists, reducing the …

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims
to align aspects and corresponding sentiments for aspect-specific sentiment polarity …

Learning effective joint embedding for cross-modal data has always been a focus in the field
of multimodal machine learning. We argue that during multimodal fusion, the generated …

Multimodal sentiment analysis is an active research field that aims to recognize the user's
sentiment information from multimodal data. The primary challenge in this field is to develop …

Human communication is multimodal in nature; it is through multiple modalities such as
language, voice, and facial expressions, that opinions and emotions are expressed. Data in …

With technological advancements, we can now capture rich dialogue content, tones, textual
information, and visual data through tools like microphones, the internet, and cameras …

We present an approach to encode a speech signal into a fixed-size representation which
minimizes the cosine loss with the existing massively multilingual LASER text embedding …