Automated audio captioning is a cross-modal translation task that aims to generate natural
language descriptions for given audio clips. This task has received increasing attention with …

The ability of artificial intelligence (AI) systems to perceive and comprehend audio signals is
crucial for many applications. Although significant progress has been made in this area …

In this paper, we propose a Vision-Audio-Language Omni-peRception pretraining model
(VALOR) for multi-modal understanding and generation. Different from widely-studied vision …

Automated audio captioning (AAC), a task that mimics human perception as well as
innovatively links audio processing and natural language processing, has overseen much …

Audio captioning aims to automatically generate a natural language description of an audio
clip. Most captioning models follow an encoder-decoder architecture, where the decoder …

Audio captioning aims to generate text descriptions from environmental sounds. One
challenge of audio captioning is the difficulty of the generalization due to the lack of audio …

In this paper, we propose the Vision-Audio-Language Omni-peRception pretraining model
(VALOR) for multimodal understanding and generation. Unlike widely-studied vision …

Automated audio captioning (AAC) aims at generating summarizing descriptions for audio
clips. Multitudinous concepts are described in an audio caption, ranging from local …

Automated audio captioning aims to use natural language to describe the content of audio
data. This paper presents an audio captioning system with an encoder-decoder architecture …

Large Language Models (LLMs) have made the ambitious quest for generalist agents
significantly far from being a fantasy. A key hurdle for building such general models is the …