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Found 9 papers, 9 papers with code
Enhancing Automated Audio Captioning via Large Language Models with Optimized Audio Encoding
Automated audio captioning (AAC) is an audio-to-text task to describe audio contents in natural language.
Ranked #2 on
Audio captioning
on Clotho
(using extra training data)
Bridging Language Gaps in Audio-Text Retrieval
The predominant focus of existing research on English descriptions poses a limitation on the applicability of such models, given the abundance of non-English content in real-world data.
Towards duration robust weakly supervised sound event detection
Our model outperforms other approaches on the DCASE2018 and URBAN-SED datasets without requiring prior duration knowledge.
Data Augmentation
Sound Event Detection
Sound
Audio and Speech Processing
Multiple Sound Sources Localization from Coarse to Fine
How to visually localize multiple sound sources in unconstrained videos is a formidable problem, especially when lack of the pairwise sound-object annotations.
Voice activity detection in the wild via weakly supervised sound event detection
We proposed two GPVAD models, one full (GPV-F), trained on 527 Audioset sound events, and one binary (GPV-B), only distinguishing speech and noise.
Sound Audio and Speech Processing
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.
Duration robust sound event detection
Task 4 of the Dcase2018 challenge demonstrated that substantially more research is needed for a real-world application of sound event detection.
Sound Audio and Speech Processing
Text-based depression detection on sparse data
Previous text-based depression detection is commonly based on large user-generated data.
Audio Caption: Listen and Tell
A baseline encoder-decoder model is provided for both English and Mandarin.
