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Scaling audio-visual learning without labels(图)     扩展视听学习  多模态技术  人工智能       font style='font-size:12px;'> 2023/6/20
Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-...
Humans observe the world through a combination of different modalities, like vision, hearing, and our understanding of language. Machines, on the other hand, interpret the world through data that algo...
Zero-resource speech processing involves the automatic analysis of a collection of speech data in a completely unsupervised fashion without the benefit of any transcriptions or annotations of the data...
In this work, we present a novel method to detect violent shots in movies. The detection process is split into two views–––the audio and video views. From the audio-view, a weakly-supervised method is...
In this paper, we present a new feature extraction algorithm which can generate robust and reliable feature in a fingerprint system. This algorithm is referred to as weighted ASF (WASF). The feature...
This conference will provide a unique forum for researchers, engineers and educators interested in audio, language and image processing to learn about recent progresses, to address related challenges ...
As a very important category in sports video, racquet sports video, e.g. table tennis, tennis and badminton, has been paid little attention in the past years. Considering the characteristics of this k...
Automatic speech recognition (ASR) performs well under restricted conditions, but performance degrades in noisy environments. Audio-Visual Speech Recognition(AVSR) combats this by incorporating a visu...

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