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10.3389/fbioe.2015.00118 http://scihub22266oqcxt.onion/10.3389/fbioe.2015.00118 C4542648!4542648!26347863     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Bioeng+Biotechnol 2015 ; 3 (ä): ä Nephropedia Template TP {{tp|p=26347863|t=2015. Adaptive Multi-Rate Compression Effects on Vowel Analysis |pdf=|usr=}}{{26347863}} gab.com Text Adaptive Multi-Rate Compression Effects on Vowel Analysis JO: Front Bioeng Biotechnol http://www.kidney.de/pget.php?&tw=1&pmid=26347863 #FOAvip Signal processing on digitally sampled vowel sounds for the detection of pathological voices has been firmly established. This work examines compression artifacts on vowel speech samples that have been compressed using the adaptive multi-rate codec at various bit-rates. Whereas previous work has used the sensitivity of machine learning algorithm to test for accuracy, this work examines the changes in the extracted speech features themselves and thus report new findings on the usefulness of a particular feature. We believe this work will have potential impact for future research on remote monitoring as the identification and exclusion of an ill-defined speech feature that has been hitherto used, will ultimately increase the robustness of the system. Twit Text FOAVip Adaptive Multi-Rate Compression Effects on Vowel Analysis ????Front Bioeng Biotechnol http://www.kidney.de/pget.php?&tw=1&pmid=26347863 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26347863 #FOAvip English Wikipedia <ref>{{Cite pmid|26347863}}</ref> Adaptive Multi-Rate Compression Effects on Vowel Analysis #MMPMID26347863 Ireland D; Knuepffer C; McBride SJ Front Bioeng Biotechnol 2015[]; 3 (ä): ä PMID26347863show ga Signal processing on digitally sampled vowel sounds for the detection of pathological voices has been firmly established. This work examines compression artifacts on vowel speech samples that have been compressed using the adaptive multi-rate codec at various bit-rates. Whereas previous work has used the sensitivity of machine learning algorithm to test for accuracy, this work examines the changes in the extracted speech features themselves and thus report new findings on the usefulness of a particular feature. We believe this work will have potential impact for future research on remote monitoring as the identification and exclusion of an ill-defined speech feature that has been hitherto used, will ultimately increase the robustness of the system. äAdaptive Multi-Rate Compression Effects on Vowel Analysis (epmc).pdf DeepDyve Pubget Overpricing