{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:39:41Z","timestamp":1750307981664,"version":"3.41.0"},"reference-count":34,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10]]},"DOI":"10.1109\/iscslp.2016.7918489","type":"proceedings-article","created":{"date-parts":[[2017,5,13]],"date-time":"2017-05-13T02:22:40Z","timestamp":1494642160000},"page":"1-5","source":"Crossref","is-referenced-by-count":1,"title":["Incorporating local environment information with ensemble neural networks to robust automatic speech recognition"],"prefix":"10.1109","author":[{"given":"Chia-Yung","family":"Hsu","sequence":"first","affiliation":[]},{"given":"Ryandhimas E.","family":"Zezario","sequence":"additional","affiliation":[]},{"given":"Jia-Ching","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chin-Wen","family":"Ho","sequence":"additional","affiliation":[]},{"given":"Xugang","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Tsao","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref32","article-title":"The Kaldi speech recognition toolkit","author":"povey","year":"2011","journal-title":"IEEE Workshop on Automatic Speech Recognition and Understanding"},{"year":"2007","key":"ref31"},{"journal-title":"Pattern Classification","year":"2001","author":"duda","key":"ref30"},{"key":"ref34","article-title":"An investigation of spectral restoration algorithms for deep neural networks based noise robust speech recognition","author":"li","year":"2013","journal-title":"Proc Interspeech'13"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"2171","DOI":"10.21437\/Eurospeech.1995-411","article-title":"Speaker-adaptation for hybrid HMM-ANN continuous speech recognition system","author":"neto","year":"1995","journal-title":"Proc EuroSpeech'95"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2006.11.005"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SLT.2012.6424251"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639201"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639212"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2013.2270370"},{"key":"ref16","article-title":"Towards speaker adaptive training of deep neural network acoustic models","author":"miao","year":"2014","journal-title":"Proc Interspeech'14"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6854826"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853585"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853591"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2009.2016231"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639345"},{"key":"ref27","article-title":"Ensemble modeling of denoising autoencoder for speech spectrum restoration","author":"lu","year":"2014","journal-title":"Proc Interspeech'14"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2011.2134090"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2014.2304637"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/89.279278"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639102"},{"key":"ref8","first-page":"92","article-title":"Improving robustness of deep neural network acoustic models via speech separation and joint adaptive training","volume":"23","author":"narayanan","year":"2015","journal-title":"IEEE Transactions on Audio Speech and Language Processing"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2014.2329237"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2011.2109382"},{"key":"ref9","article-title":"A long, deep and wide artificial neural net for robust speech recognition in unknown noise","author":"li","year":"2014","journal-title":"Proc Interspeech'14"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2205597"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/34.58871"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(02)00190-X"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.1.79"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300015178"},{"key":"ref26","article-title":"The Aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions","author":"pearce","year":"2000","journal-title":"ASR2000 Automatic Speech Recognition Challenges for the new Millenium ISCA Tutorial and Research Workshop"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2013.11.005"}],"event":{"name":"2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP)","start":{"date-parts":[[2016,10,17]]},"location":"Tianjin, China","end":{"date-parts":[[2016,10,20]]}},"container-title":["2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7912121\/7918361\/07918489.pdf?arnumber=7918489","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T15:01:13Z","timestamp":1750258873000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7918489\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,10]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/iscslp.2016.7918489","relation":{},"subject":[],"published":{"date-parts":[[2016,10]]}}}