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 …

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 at describing the content of audio clips with human language. Due to
the ambiguity of audio content, different people may perceive the same audio clip differently …

State-of-the-art audio captioning methods typically use the encoder-decoder structure with
pretrained audio neural networks (PANNs) as encoders for feature extraction. However, the …

We propose EnCLAP, a novel framework for automated audio captioning. EnCLAP employs
two acoustic representation models, EnCodec and CLAP, along with a pretrained language …

Automated audio captioning is a cross-modal translation task for describing the content of
audio clips with natural language sentences. This task has attracted increasing attention and …

The growth of plants is threatened by numerous diseases. Accurate and timely identification
of these diseases is crucial to prevent disease spreading. Many deep learning-based …

Data-driven approaches hold promise for audio captioning. However, the development of
audio captioning methods can be biased due to the limited availability and quality of text …

The weakly-supervised audio-visual video parsing (AVVP) task aims toparse a video into
temporal events and predict their modality-specific categories. Current works primarily focus …

Generating both diverse and accurate descriptions is an essential goal in the audio
captioning task. Traditional methods mainly focus on improving the accuracy of the …