Home Console Docs News Papers Tutorials Datasets Wiki SOTA LLM Models GPU Leaderboard Events

English

Audio Captioning On Audiocaps

Metrics

CIDEr

METEOR

SPICE

SPIDEr

Results

Performance results of various models on this benchmark

					Paper Title	Repository
SLAM-AAC	0.841	0.268	0.194	0.518	SLAM-AAC: Enhancing Audio Captioning with Paraphrasing Augmentation and CLAP-Refine through LLMs
AutoCap	0.832	0.253	0.182	0.507	Taming Data and Transformers for Audio Generation
EnCLAP++-large	0.823	0.269	0.197	0.510	EnCLAP++: Analyzing the EnCLAP Framework for Optimizing Automated Audio Captioning Performance
LOAE	0.816	0.267	0.193	0.505	Enhancing Automated Audio Captioning via Large Language Models with Optimized Audio Encoding
EnCLAP++-base	0.815	0.257	0.188	0.501	EnCLAP++: Analyzing the EnCLAP Framework for Optimizing Automated Audio Captioning Performance
CNext-trans	0.8061	0.2527	0.1841	0.4951	-	-
EnCLAP-large	0.8029	0.2554	0.1879	0.4954	EnCLAP: Combining Neural Audio Codec and Audio-Text Joint Embedding for Automated Audio Captioning
VAST	0.781	0.247	-	-	VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset
EnCLAP-base	0.7795	0.2473	0.1863	0.4829	EnCLAP: Combining Neural Audio Codec and Audio-Text Joint Embedding for Automated Audio Captioning
AL-MixGen + Multi-TTA	0.769	-	0.181	0.475	-	-
Rethink-ACT (AST + TF + MIL)	0.764	0.242	0.180	0.472	Rethinking Transfer and Auxiliary Learning for Improving Audio Captioning Transformer	-
AL-MixGen	0.755	-	0.177	0.466	Exploring Train and Test-Time Augmentations for Audio-Language Learning	-
BART + YAMNet + PANNs	0.753	-	0.176	0.465	AUTOMATED AUDIO CAPTIONING BY FINE-TUNING BART WITH AUDIOSET TAGS	-
VALOR	0.741	0.231	-	-	VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
CNN+Transformer	0.693	-	0.159	0.426	Audio Captioning Transformer
TopDown-AlignedAtt (1NN)	0.593	-	0.144	0.369	AudioCaps: Generating Captions for Audios in The Wild	-

0 of 16 row(s) selected.

Audio Captioning On Audiocaps | SOTA | HyperAI