AVR: Synergizing Foundation Models for Audio-Visual Humor Detection

Autor:	Sharma, Sarthak, Phukan, Orchid Chetia, Singh, Drishti, Buduru, Arun Balaji, Sharma, Rajesh
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Audio and Speech Processing Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	In this work, we present, AVR application for audio-visual humor detection. While humor detection has traditionally centered around textual analysis, recent advancements have spotlighted multimodal approaches. However, these methods lean on textual cues as a modality, necessitating the use of ASR systems for transcribing the audio-data. This heavy reliance on ASR accuracy can pose challenges in real-world applications. To address this bottleneck, we propose an innovative audio-visual humor detection system that circumvents textual reliance, eliminating the need for ASR models. Instead, the proposed approach hinges on the intricate interplay between audio and visual content for effective humor detection. Comment: Accepted to INTERSPEECH 2024 Show & Tell Demonstrations
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2406.10448 Zobrazit plný text záznamu View this record from Arxiv