الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Audio Captioning On Audiocaps

المقاييس

CIDEr

METEOR

SPICE

SPIDEr

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

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

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