{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T14:47:57Z","timestamp":1746456477054},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319633145"},{"type":"electronic","value":"9783319633152"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-63315-2_59","type":"book-chapter","created":{"date-parts":[[2017,7,20]],"date-time":"2017-07-20T04:48:34Z","timestamp":1500526114000},"page":"672-681","source":"Crossref","is-referenced-by-count":2,"title":["Lying Speech Characteristic Extraction Based on SSAE Deep Learning Model"],"prefix":"10.1007","author":[{"given":"Yan","family":"Zhou","sequence":"first","affiliation":[]},{"given":"Heming","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Li","family":"Shang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,7,21]]},"reference":[{"key":"59_CR1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.dss.2015.04.006","volume":"74","author":"C Throckmorton","year":"2015","unstructured":"Throckmorton, C., Handra, S., William, J.: Financial fraud detection using vocal, linguistic and financial cues. Decis. Support Syst. 74, 78\u201387 (2015)","journal-title":"Decis. Support Syst."},{"issue":"4","key":"59_CR2","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1037\/xap0000102","volume":"22","author":"E Elliott","year":"2016","unstructured":"Elliott, E., Leach, A.M.: You must be lying because i don\u2019t understand you: language proficiency and lie detection. J. Exp. Psychol. Appl. 22(4), 488\u2013499 (2016)","journal-title":"J. Exp. Psychol. Appl."},{"issue":"4","key":"59_CR3","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1109\/TASL.2012.2229986","volume":"21","author":"XL Zhang","year":"2013","unstructured":"Zhang, X.L., Wu, J.: Deep belief networks based voice activity detection. IEEE Trans. Audio Speech Lang. Process. 21(4), 697\u2013710 (2013)","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"59_CR4","first-page":"2949","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Salakhutdinov, R.: Multimodal learning with deep boltzmann machines. J. Mach. Learn. Res. 15, 2949\u20132980 (2014)","journal-title":"J. Mach. Learn. Res."},{"issue":"10","key":"59_CR5","first-page":"2496","volume":"27","author":"PP Brahma","year":"2015","unstructured":"Brahma, P.P., Wu, D.P., She, Y.Y.: Why deep learning works: a manifold disentanglement perspective. IEEE Trans. Neural Netw. Learn. Syst. 27(10), 2496\u20132947 (2015)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"6","key":"59_CR6","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/MSP.2012.2205597","volume":"29","author":"GE Hinton","year":"2012","unstructured":"Hinton, G.E., Li, D., et al.: Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups. Sig. Process. Mag. 29(6), 82\u201397 (2012)","journal-title":"Sig. Process. Mag."},{"issue":"7","key":"59_CR7","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.W.: A fast learning algorithm for deep belief nets. Neural Comput. 18(7), 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"59_CR8","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.neucom.2014.07.087","volume":"170","author":"XG Li","year":"2015","unstructured":"Li, X.G., Yang, Y.N., Pang, Z.H.: A comparative study on selecting acoustic modeling units in deep neural networks based large vocabulary Chinese speech recognition. Neurocomputing 170, 251\u2013256 (2015)","journal-title":"Neurocomputing"},{"issue":"8","key":"59_CR9","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1109\/TASLP.2016.2558822","volume":"24","author":"J Du","year":"2016","unstructured":"Du, J., Tu, Y.H., Dai, L.R.: A regression approach to single-channel speech separation via high-resolution deep neural networks. IEEE-ACM Trans. Audio Speech Lang. Process. 24(8), 1424\u20131437 (2016)","journal-title":"IEEE-ACM Trans. Audio Speech Lang. Process."},{"key":"59_CR10","doi-asserted-by":"crossref","unstructured":"Jaitly, N., Hinton, G.E.: Using an auto encoder with deform-able templates to discover features for automated speech recognition. In: 14th Annual Conference of the International Speech Communication Association, Lyon, pp. 25\u201329 (2013)","DOI":"10.21437\/Interspeech.2013-432"},{"key":"59_CR11","doi-asserted-by":"crossref","unstructured":"Cai, M., Shi, Y., Liu, J.: Deep maxout neural networks for speech recognition. In: Workshop on IEEE International Proceedings on the Automatic Speech Recognition and Understanding, pp. 291\u2013296 (2013)","DOI":"10.1109\/ASRU.2013.6707745"},{"key":"59_CR12","unstructured":"Chen, M.M.: Fusion of various characteristics of Chinese speech recognition based on the technology of deep learning. Doctoral dissertation of University of Chinese Academy of Sciences, Beijing (2015)"},{"issue":"12","key":"59_CR13","doi-asserted-by":"crossref","first-page":"2112","DOI":"10.1109\/TASLP.2014.2361023","volume":"22","author":"Y Jiang","year":"2014","unstructured":"Jiang, Y., Wang, D.L., Liu, R.S.: Binaural classification for reverberant speech segregation using deep neural networks. IEEE-ACM Trans. Audio Speech Lang. Process. 22(12), 2112\u20132121 (2014)","journal-title":"IEEE-ACM Trans. Audio Speech Lang. Process."}],"container-title":["Lecture Notes in Computer Science","Intelligent Computing Methodologies"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-63315-2_59","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T02:13:07Z","timestamp":1659233587000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-63315-2_59"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319633145","9783319633152"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-63315-2_59","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]}}}