{"title":"线性PCM音频的鲁棒超低延迟软判决解码","authors":"Florian Pflug, T. Fingscheidt","doi":"10.1109/TASL.2013.2273716","DOIUrl":null,"url":null,"abstract":"Applications such as professional wireless digital microphones require a transmission of practically uncoded high-quality audio with ultra-low latency on the one hand and robustness to error-prone channels on the other hand. The delay restrictions, however, prohibit the utilization of efficient block or convolutional channel codes for error protection. The contribution of this work is fourfold: We revise and summarize concisely a Bayesian framework for soft-decision audio decoding and present three novel approaches to (almost) latency-free robust decoding of uncompressed audio. Bit reliability information from the transmission channel is exploited, as well as short-term and long-term residual redundancy within the audio signal, and optionally some explicit redundancy in terms of a sample-individual block code. In all cases we utilize variants of higher-order linear prediction to compute prediction probabilities in three novel ways: Firstly by employing a serial cascade of multiple predictors, secondly by exploiting explicit redundancy in form of parity bits, and thirdly by utilizing an interpolative forward/backward prediction algorithm. The first two presented approaches work fully delayless, while the third one introduces an ultra-low algorithmic delay of just a few samples. The effectiveness of the proposed algorithms is proven in simulations with BPSK and typical digital microphone FSK modulation schemes on AWGN and bursty fading channels.","PeriodicalId":55014,"journal":{"name":"IEEE Transactions on Audio Speech and Language Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TASL.2013.2273716","citationCount":"11","resultStr":"{\"title\":\"Robust Ultra-Low Latency Soft-Decision Decoding of Linear PCM Audio\",\"authors\":\"Florian Pflug, T. Fingscheidt\",\"doi\":\"10.1109/TASL.2013.2273716\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Applications such as professional wireless digital microphones require a transmission of practically uncoded high-quality audio with ultra-low latency on the one hand and robustness to error-prone channels on the other hand. The delay restrictions, however, prohibit the utilization of efficient block or convolutional channel codes for error protection. The contribution of this work is fourfold: We revise and summarize concisely a Bayesian framework for soft-decision audio decoding and present three novel approaches to (almost) latency-free robust decoding of uncompressed audio. Bit reliability information from the transmission channel is exploited, as well as short-term and long-term residual redundancy within the audio signal, and optionally some explicit redundancy in terms of a sample-individual block code. In all cases we utilize variants of higher-order linear prediction to compute prediction probabilities in three novel ways: Firstly by employing a serial cascade of multiple predictors, secondly by exploiting explicit redundancy in form of parity bits, and thirdly by utilizing an interpolative forward/backward prediction algorithm. The first two presented approaches work fully delayless, while the third one introduces an ultra-low algorithmic delay of just a few samples. The effectiveness of the proposed algorithms is proven in simulations with BPSK and typical digital microphone FSK modulation schemes on AWGN and bursty fading channels.\",\"PeriodicalId\":55014,\"journal\":{\"name\":\"IEEE Transactions on Audio Speech and Language Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/TASL.2013.2273716\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Audio Speech and Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TASL.2013.2273716\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Audio Speech and Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TASL.2013.2273716","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust Ultra-Low Latency Soft-Decision Decoding of Linear PCM Audio
Applications such as professional wireless digital microphones require a transmission of practically uncoded high-quality audio with ultra-low latency on the one hand and robustness to error-prone channels on the other hand. The delay restrictions, however, prohibit the utilization of efficient block or convolutional channel codes for error protection. The contribution of this work is fourfold: We revise and summarize concisely a Bayesian framework for soft-decision audio decoding and present three novel approaches to (almost) latency-free robust decoding of uncompressed audio. Bit reliability information from the transmission channel is exploited, as well as short-term and long-term residual redundancy within the audio signal, and optionally some explicit redundancy in terms of a sample-individual block code. In all cases we utilize variants of higher-order linear prediction to compute prediction probabilities in three novel ways: Firstly by employing a serial cascade of multiple predictors, secondly by exploiting explicit redundancy in form of parity bits, and thirdly by utilizing an interpolative forward/backward prediction algorithm. The first two presented approaches work fully delayless, while the third one introduces an ultra-low algorithmic delay of just a few samples. The effectiveness of the proposed algorithms is proven in simulations with BPSK and typical digital microphone FSK modulation schemes on AWGN and bursty fading channels.
期刊介绍:
The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.