Pub Date : 2018-08-09DOI: 10.1017/9780511756597.023
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Pub Date : 2018-08-09DOI: 10.1017/9780511756597.007
E. Park
In this paper, the perceived loudness metering algorithm based on ITU-R BS.1387-1 was investigated and implemented, and its performance was evaluated by applying to 23 pure tones and 9 digital audio samples. Error of the tone test results compared with ISO226:2003 was below 5%, and sample test results, in comparison with Moore's algorithm, showed deviation of less than 4.7% and correlation of 0.96. On the other hand, it was investigated how the implemented algorithm's performance was subject to auditory pitch scale. Its result showed that the algorithm with 37 auditory filters, through correcting a bias effect, has a good performance of less than 2% in comparison with the one with 109 auditory filters. 요 약 본 논문에서는 객관적 오디오 품질 분석에 대한 권고안인 ITU-R BS.1387-1의 귀의 모델을 토대로 라우드니스를 객관적으로 측정할 수 있는 알고리즘을 구현하며, 그 성능을 23개의 순음과 9개의 샘플 디지털 사운드에 적용하여 평가하였다. 순음의 경우 ISO226:2003에서 제공하는 실험 데이터와 비교한 결과 5%이하의 오차를 보이며, 디지털 사운드 실험 결과도 Moore 모델의 측정결과와 비교할 때 4.7%이하의 편차와 0.96이상의 코릴레이션을 나타내어 좋은 성능을 보였다. 한편 구현 알고리즘에 적용한 청각필터 수에 따른 성능 변화를 분석하기 위해 21개의 별도의 샘플 디지털 사운드에 적용하였다. 그 결과를 분석하여 보면, 37개의 청각필터를 갖는 구현 알고리즘에 바이어스 보상값을 적용함으로써 109개 필터를 사용하는 경우에 대해 2%미만의 오차를 갖는 양호한 성능을 갖도록 할 수 있었다.
In this paper, the perceived loudness metering algorithm based on ITU-R BS.1387-1 was investigated and implemented;and its performance was evaluated by applying to 23 pure tones and 9 digital audio samples。Error of the tone test results compared with ISO226:2003 was below 5%， and sample test results, in comparison with Moore's algorithm, showed deviation of less than 4.7% and correlation of 0.96。On the other hand, it was investigated how the implemented algorithm's performance was subject to auditory pitch scale。Its result showed that the algorithm with 37 auditory filters, through correcting a bias effect, has a good performance of less than 2% in comparison with the one with 109 auditory filters。姚约本论文以建议客观音频质量分析的ITU-R BS.1387-1的耳朵模型为基础，体现了可以客观测定loudness的算法，并将其性能应用于23个纯音和9个样本数字声音中进行了评价。纯音的情况是，与ISO226:2003提供的实验数据进行比较的结果，误差在5%以下，数字声音实验结果与Moore模型的测定结果相比，偏差在4.7%以下和0.96以上，表现出良好的性能。另外，为了分析听觉过滤器数量对实现算法的性能变化，应用于21个不同的样本数字声音。分析结果显示，对具有37个听觉过滤器的实现算法使用斜杠补偿值，使109个过滤器的误差不到2%，具有良好的性能。
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Pub Date : 2018-08-09DOI: 10.1017/9780511756597.025
{"title":"Preface to New York Edition","authors":"","doi":"10.1017/9780511756597.025","DOIUrl":"https://doi.org/10.1017/9780511756597.025","url":null,"abstract":"","PeriodicalId":228579,"journal":{"name":"The Reverberator","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123688802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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