Acoustic Event Detection with Classifier Chains

التفاصيل البيبلوغرافية
العنوان: Acoustic Event Detection with Classifier Chains
المؤلفون: Komatsu, Tatsuya, Watanabe, Shinji, Miyazaki, Koichi, Hayashi, Tomoki
سنة النشر: 2022
المجموعة: Computer Science
مصطلحات موضوعية: Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Sound
الوصف: This paper proposes acoustic event detection (AED) with classifier chains, a new classifier based on the probabilistic chain rule. The proposed AED with classifier chains consists of a gated recurrent unit and performs iterative binary detection of each event one by one. In each iteration, the event's activity is estimated and used to condition the next output based on the probabilistic chain rule to form classifier chains. Therefore, the proposed method can handle the interdependence among events upon classification, while the conventional AED methods with multiple binary classifiers with a linear layer and sigmoid function have placed an assumption of conditional independence. In the experiments with a real-recording dataset, the proposed method demonstrates its superior AED performance to a relative 14.80% improvement compared to a convolutional recurrent neural network baseline system with the multiple binary classifiers.
Comment: 5pages, presented at Interspeech2021
نوع الوثيقة: Working Paper
DOI: 10.21437/Interspeech.2021-2218
URL الوصول: http://arxiv.org/abs/2202.08470
رقم الأكسشن: edsarx.2202.08470
قاعدة البيانات: arXiv
الوصف
DOI:10.21437/Interspeech.2021-2218