Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new environmental sound classification architecture. The proposed sound classifier is performed in frame level and fuses the support vector machine (SVM) and the k nearest neighbor rule (KNN). In feature selection, three MPEG-7 audio low-level descriptors, spectrum centroid, spectrum spread, and spectrum flatness are used as the sound features to exploit their ability in sound classification. Experiments carried out on 12-class sound database can achieve an 85.1% accuracy rate. The The The performance comparison beten the HMM sound classifier using audio spectrum projection features demonstrates the superiority of the proposed scheme.
['Jia-Ching Wang', 'Jhing-Fa Wang', 'Kuok Wai He', 'Cheng-Shu Hsu']
I am writing a research paper on a idea Environmental Sound Classification using Hybrid SVM/KNN Classifier and MPEG-7 Audio Low-Level Descriptor
[{"from": "human", "value": "I am writing a research paper on a idea Environmental Sound Classification using Hybrid SVM/KNN Classifier and MPEG-7 Audio Low-Level Descriptor"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new environmental sound classification architecture. The proposed sound classifier is performed in frame level and fuses the support vector machine (SVM) and the k nearest neighbor rule (KNN). In feature selection, three MPEG-7 audio low-level descriptors, spectrum centroid, spectrum spread, and spectrum flatness are used as the sound features to exploit their ability in sound classification. Experiments carried out on 12-class sound database can achieve an 85.1% accuracy rate. The The The performance comparison beten the HMM sound classifier using audio spectrum projection features demonstrates the superiority of the proposed scheme."}]