{"title":"利用相位差分离声源和可靠掩模选择","authors":"Chanwoo Kim, Anjali Menon, M. Bacchiani, R. Stern","doi":"10.1109/ICASSP.2018.8462269","DOIUrl":null,"url":null,"abstract":"We present an algorithm called Reliable Mask Selection-Phase Difference Channel Weighting (RMS-PDCW) which selects the target source masked by a noise source using the Angle of Arrival (AoA) information calculated using the phase difference information. The RMS-PDCW algorithm selects masks to apply using the information about the localized sound source and the onset detection of speech. We demonstrate that this algorithm shows relatively 5.3 percent improvement over the baseline acoustic model, which was multistyle-trained using 22 million utterances on the simulated test set consisting of real-world and interfering-speaker noise with reverberation time distribution between 0 ms and 900 ms and SNR distribution between 0 dB up to clean.","PeriodicalId":6638,"journal":{"name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"110 1","pages":"5559-5563"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Sound Source Separation Using Phase Difference and Reliable Mask Selection Selection\",\"authors\":\"Chanwoo Kim, Anjali Menon, M. Bacchiani, R. Stern\",\"doi\":\"10.1109/ICASSP.2018.8462269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an algorithm called Reliable Mask Selection-Phase Difference Channel Weighting (RMS-PDCW) which selects the target source masked by a noise source using the Angle of Arrival (AoA) information calculated using the phase difference information. The RMS-PDCW algorithm selects masks to apply using the information about the localized sound source and the onset detection of speech. We demonstrate that this algorithm shows relatively 5.3 percent improvement over the baseline acoustic model, which was multistyle-trained using 22 million utterances on the simulated test set consisting of real-world and interfering-speaker noise with reverberation time distribution between 0 ms and 900 ms and SNR distribution between 0 dB up to clean.\",\"PeriodicalId\":6638,\"journal\":{\"name\":\"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"volume\":\"110 1\",\"pages\":\"5559-5563\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2018.8462269\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2018.8462269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sound Source Separation Using Phase Difference and Reliable Mask Selection Selection
We present an algorithm called Reliable Mask Selection-Phase Difference Channel Weighting (RMS-PDCW) which selects the target source masked by a noise source using the Angle of Arrival (AoA) information calculated using the phase difference information. The RMS-PDCW algorithm selects masks to apply using the information about the localized sound source and the onset detection of speech. We demonstrate that this algorithm shows relatively 5.3 percent improvement over the baseline acoustic model, which was multistyle-trained using 22 million utterances on the simulated test set consisting of real-world and interfering-speaker noise with reverberation time distribution between 0 ms and 900 ms and SNR distribution between 0 dB up to clean.