{"title":"基于时域特征的膜板声检测置信度测度","authors":"M. Schlosser","doi":"10.1109/ICASSP.2008.4517565","DOIUrl":null,"url":null,"abstract":"An acoustic detector for film slates is proposed to assist a human operator with the synchronization of audio and video in post-production. To be computationally efficient, the signal analysis is restricted to time-domain features. Although the features are statistically dependent, separate classifiers are trained for each of them. The statistical dependence is taken into account during the combination of the log-likelihood ratios provided by the individual classifiers. The overall confidence in a classification is determined as a weighted sum of the individual log-likelihood ratios, where the weights depend on the correlation between the different features. Experimental results for real-world recordings from film sets show that the confidence measures allow for a fast identification of the film slates while minimizing the interference from false detections.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Confidence measures for acoustic detection of film slates based on time-domain features\",\"authors\":\"M. Schlosser\",\"doi\":\"10.1109/ICASSP.2008.4517565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An acoustic detector for film slates is proposed to assist a human operator with the synchronization of audio and video in post-production. To be computationally efficient, the signal analysis is restricted to time-domain features. Although the features are statistically dependent, separate classifiers are trained for each of them. The statistical dependence is taken into account during the combination of the log-likelihood ratios provided by the individual classifiers. The overall confidence in a classification is determined as a weighted sum of the individual log-likelihood ratios, where the weights depend on the correlation between the different features. Experimental results for real-world recordings from film sets show that the confidence measures allow for a fast identification of the film slates while minimizing the interference from false detections.\",\"PeriodicalId\":333742,\"journal\":{\"name\":\"2008 IEEE International Conference on Acoustics, Speech and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Acoustics, Speech and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2008.4517565\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2008.4517565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Confidence measures for acoustic detection of film slates based on time-domain features
An acoustic detector for film slates is proposed to assist a human operator with the synchronization of audio and video in post-production. To be computationally efficient, the signal analysis is restricted to time-domain features. Although the features are statistically dependent, separate classifiers are trained for each of them. The statistical dependence is taken into account during the combination of the log-likelihood ratios provided by the individual classifiers. The overall confidence in a classification is determined as a weighted sum of the individual log-likelihood ratios, where the weights depend on the correlation between the different features. Experimental results for real-world recordings from film sets show that the confidence measures allow for a fast identification of the film slates while minimizing the interference from false detections.