Skip to Main Content
Automatic Language Identification (LID) in music has received significantly less attention than LID in speech. Here, we study the problem of LID in music videos uploaded on YouTube. We use a "bag-of-words" approach based on state-of-the-art content based audio-visual features and linear S VM classifiers for automatic LID. Our system obtains 48% accuracy for a corpus of 25000 music videos and 25 different languages.