cross-modal model between audio(MFCC) and text(KoBERT) - audiotext-transformer/datasets.py at master · Donghwa-KIM/audiotext-transformer.
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pytorch cross-modal Transformer using two features: MFCC from audio signal (1-channel); BERT last layer fine-tuned by multi-sentiment dataset. Requirements.
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Multimodal Transformer for Korean Sentiment Analysis with Audio and Text Features - youngbin-ro/audiotext-transformer.
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cross-modal model between audio(MFCC) and text(KoBERT) - audiotext-transformer/utils.py at master · Donghwa-KIM/audiotext-transformer.
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cross-modal model between audio(MFCC) and text(KoBERT) - audiotext-transformer/modules.py at master · Donghwa-KIM/audiotext-transformer.
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The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection", in ICASSP 2022.
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This volume contains the papers selected for presentation at the 26th International. Symposium on Methodologies for Intelligent Systems (ISMIS 2022), ...
All the experiments were carried out on AudioCaps dataset, which is sourced from AudioSet. Our download version contains 49274/49837 audio clips in training set ...
Missing: carat q= https:// Donghwa- KIM/ audiotext- blob/ master/
Multimodal Transformer for Korean Sentiment Analysis with Audio and Text Features - audiotext-transformer/model.py at master ...
Missing: carat audio/ url? q= https:// Donghwa- KIM/ datasets.
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