{"title":"A study of the perceptual relevance of the burst phase of stop consonants with implications in speech coding","authors":"Vincent Santini, P. Gournay, R. Lefebvre","doi":"10.1109/MMSP.2016.7813374","DOIUrl":null,"url":null,"abstract":"Stop consonants are an important constituent of the speech signal. They contribute significantly to its intelligibility and subjective quality. However, because of their dynamic and unpredictable nature, they tend to be difficult to encode using conventional approaches such as linear predictive coding and transform coding. This paper presents a system to detect, segment, and modify stop consonants in a speech signal. This system is then used to assess the following hypothesis: Muting the burst phase of stop consonants has a negligible impact on the subjective quality of speech. The muting operation is implemented and its impact on subjective quality is evaluated on a database of speech signals. The results show that this apparently drastic alteration has in reality very little perceptual impact. The implications for speech coding are then discussed.","PeriodicalId":113192,"journal":{"name":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","volume":"PP 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2016.7813374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Stop consonants are an important constituent of the speech signal. They contribute significantly to its intelligibility and subjective quality. However, because of their dynamic and unpredictable nature, they tend to be difficult to encode using conventional approaches such as linear predictive coding and transform coding. This paper presents a system to detect, segment, and modify stop consonants in a speech signal. This system is then used to assess the following hypothesis: Muting the burst phase of stop consonants has a negligible impact on the subjective quality of speech. The muting operation is implemented and its impact on subjective quality is evaluated on a database of speech signals. The results show that this apparently drastic alteration has in reality very little perceptual impact. The implications for speech coding are then discussed.