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Found 8 papers, 3 papers with code
SemantiCodec: An Ultra Low Bitrate Semantic Audio Codec for General Sound
Large language models (LLMs) have significantly advanced audio processing through audio codecs that convert audio into discrete tokens, enabling the application of language modelling techniques to audio data.
T-CLAP: Temporal-Enhanced Contrastive Language-Audio Pretraining
Contrastive language-audio pretraining~(CLAP) has been developed to align the representations of audio and language, achieving remarkable performance in retrieval and classification tasks.
A Large-scale Dataset for Audio-Language Representation Learning
To tackle these challenges, we present an innovative and automatic audio caption generation pipeline based on a series of public tools or APIs, and construct a large-scale, high-quality, audio-language dataset, named as Auto-ACD, comprising over 1. 9M audio-text pairs.
Improving Audio Caption Fluency with Automatic Error Correction
Automated audio captioning (AAC) is an important cross-modality translation task, aiming at generating descriptions for audio clips.
Can Audio Captions Be Evaluated with Image Caption Metrics?
Current metrics are found in poor correlation with human annotations on these datasets.
THE SJTU SYSTEM FOR DCASE2021 CHALLENGE TASK 6: AUDIO CAPTIONING BASED ON ENCODER PRE-TRAINING AND REINFORCEMENT LEARNING
This report proposes an audio captioning system for the Detection and Classification of Acoustic Scenes and Events (DCASE) 2021 challenge task Task 6.
Ranked #2 on
Audio captioning
on Clotho
(using extra training data)
Audio Caption in a Car Setting with a Sentence-Level Loss
Captioning has attracted much attention in image and video understanding while a small amount of work examines audio captioning.
