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Audio Captioning On Clotho

Metrics

BLEU-4
CIDEr
METEOR
ROUGE-L

Results

Performance results of various models on this benchmark

Paper TitleRepository
VAST190.51919.340.8VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset
SLAM-AAC-0.5150.197-SLAM-AAC: Enhancing Audio Captioning with Paraphrasing Augmentation and CLAP-Refine through LLMs
LOAE-0.5130.197-Enhancing Automated Audio Captioning via Large Language Models with Optimized Audio Encoding
Audio Flamingo (Pengi trainset)17.40.48918.739.4Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Ensemble-RL-0.468--THE SJTU SYSTEM FOR DCASE2021 CHALLENGE TASK 6: AUDIO CAPTIONING BASED ON ENCODER PRE-TRAINING AND REINFORCEMENT LEARNING-
Qwen-Audio-0.441--Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models
VALOR16.20.42317.438.2VALOR: Vision-Audio-Language Omni-Perception Pretraining Model and Dataset
Ensemble-0.400--THE DCASE 2021 CHALLENGE TASK 6 SYSTEM: AUTOMATED AUDIO CAPTIONING WITH WEAKLY SUPERVISED PRE-TRAING AND WORD SELECTION METHODS-
Ensemble-0.319--The NTT DCASE2020 Challenge Task 6 system: Automated Audio Captioning with Keywords and Sentence Length Estimation-
RNN-GRU-EncDec + VGGish + Word2Vec-0.18--Audio Captioning using Gated Recurrent Units-
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