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</style><b data-mce-style="mso-bidi-font-weight: normal;" style="mso-bidi-font-weight: normal;"><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;">Research engineer or post-doc position in Natural Language Processing: Introduction of semantic information in a speech recognition system</span></b></div><div><b data-mce-style="mso-bidi-font-weight: normal;" style="mso-bidi-font-weight: normal;"><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;"><br data-mce-bogus="1"></span></b></div><div><br></div><div><b data-mce-style="mso-bidi-font-weight: normal;" style="mso-bidi-font-weight: normal;"><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;">Supervisors:</span></b><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;"> Irina Illina, MdC, Dominique Fohr, CR CNRS</span></div><div data-marker="__QUOTED_TEXT__"><div><br></div><div><b data-mce-style="mso-bidi-font-weight: normal;" style="mso-bidi-font-weight: normal;"><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;">Team:</span></b><span lang="EN-US" data-mce-style="mso-ansi-language: EN-US;" style="mso-ansi-language: EN-US;"> Multispeech, LORIA-INRIA (https://team.inria.fr/multispeech/)</span><br></div><div id="zimbraEditorContainer" style="font-family: arial, helvetica, sans-serif; font-size: 12pt; color: #000000;" class="2" data-mce-style="font-family: arial, helvetica, sans-serif; font-size: 12pt; color: #000000;"><div><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Contact:</span></b><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"> illina@loria.fr, dominique.fohr@loria.fr</span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Duration:</span></b><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"> 12-15 months</span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Deadline to apply</span></b><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"> : December 20th, 2019</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Required skills:</span></b><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"> Strong background in mathematics, machine learning (DNN), statistics, natural language processing and computer program skills (Perl, Python). </span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">Following profiles are welcome, either:</span></p><p class="MsoListParagraph" style="text-indent: -18pt; margin: 0px;" data-mce-style="text-indent: -18pt; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol; mso-ansi-language: EN-US;" data-mce-style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol; mso-ansi-language: EN-US;"><span style="mso-list: Ignore;" data-mce-style="mso-list: Ignore;">·<span style="font-style: normal; font-variant: normal; font-weight: normal; font-stretch: normal; line-height: normal; font-family: 'Times New Roman';" data-mce-style="font-style: normal; font-variant: normal; font-weight: normal; font-stretch: normal; line-height: normal; font-family: 'Times New Roman';"> </span></span></span><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Strong background in signal processing</span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">or</span></p><p class="MsoListParagraph" style="text-indent: -18pt; margin: 0px;" data-mce-style="text-indent: -18pt; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><span lang="EN-US" style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol; mso-ansi-language: EN-US;" data-mce-style="font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol; mso-ansi-language: EN-US;"><span style="mso-list: Ignore;" data-mce-style="mso-list: Ignore;">·<span style="font-style: normal; font-variant: normal; font-weight: normal; font-stretch: normal; line-height: normal; font-family: 'Times New Roman';" data-mce-style="font-style: normal; font-variant: normal; font-weight: normal; font-stretch: normal; line-height: normal; font-family: 'Times New Roman';"> </span></span></span><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Strong experience with natural language processing</span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">Excellent English writing and speaking skills are required in any case.<span style="mso-spacerun: yes;" data-mce-style="mso-spacerun: yes;"> </span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">Candidates should email a detailed CV with diploma</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"> </span></p><p style="margin: 0px; text-align: justify;" data-mce-style="margin: 0px; text-align: justify;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;">LORIA</span></b><span lang="EN-US" style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;"> is the French acronym for the “Lorraine Research Laboratory in Computer Science and its Applications” and is a research unit (UMR 7503), common to </span><span style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;"><a href="http://www.cnrs.fr/index.php" style="box-sizing: border-box;" target="_blank" data-mce-style="box-sizing: border-box;"><span lang="EN-US" style="color: #d569ab; mso-ansi-language: EN-US;" data-mce-style="color: #d569ab; mso-ansi-language: EN-US;">CNRS</span></a></span><span lang="EN-US" style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;">, the </span><span style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;"><a href="http://vers.univ-lorraine.fr/" style="box-sizing: border-box;" target="_blank" data-mce-style="box-sizing: border-box;"><span lang="EN-US" style="color: #d569ab; mso-ansi-language: EN-US;" data-mce-style="color: #d569ab; mso-ansi-language: EN-US;">University of Lorraine</span></a></span><span lang="EN-US" style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;"> and </span><span style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;"><a href="http://www.inria.fr/en/" style="box-sizing: border-box;" target="_blank" data-mce-style="box-sizing: border-box;"><span lang="EN-US" style="color: #d569ab; mso-ansi-language: EN-US;" data-mce-style="color: #d569ab; mso-ansi-language: EN-US;">INRIA</span></a></span><span lang="EN-US" style="font-family: Calibri, sans-serif; color: #333333;" data-mce-style="font-family: Calibri, sans-serif; color: #333333;">. This unit was officially created in 1997. Loria’s missions mainly deal with fundamental and applied research in computer sciences.</span></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"> </span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">MULTISPEECH</span></b><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"> is a joint research team between the Université of Lorraine, Inria, and CNRS. Its research focuses on speech processing, with particular emphasis to multisource (source separation, robust speech recognition), multilingual (computer assisted language learning), and multimodal aspects (audiovisual synthesis).</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"><br></span></b></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Context and objectives</span></b></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><br></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">Under noisy conditions, audio acquisition is one of the toughest challenges to have a successful automatic speech recognition (ASR). Much of the success relies on the ability to attenuate ambient noise in the signal and to take it into account in the acoustic model used by the ASR. Our DNN (Deep Neural Network) denoising system and our approach to exploiting uncertainties have shown their combined effectiveness against noisy speech.</span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"> The ASR stage will be supplemented by a semantic analysis. Predictive representations using continuous vectors have been shown to capture the semantic characteristics of words and their context, and to overcome representations based on counting words. Semantic analysis will be performed by combining predictive representations using continuous vectors and uncertainty on denoising. This combination will be done by the rescoring component. All our models will be based on the powerful technologies of DNN.</span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">The performances of the various modules will be evaluated on artificially noisy speech signals and on real noisy data. At the end, a demonstrator, integrating all the modules, will be set up.</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"><br></span></b></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">Main activities</span></b></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><br></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">• study and implementation of a noisy speech enhancement module and a propagation of uncertainty module;</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">• design a semantic analysis module;</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;">• design a module taking into account the semantic and uncertainty information.</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;"><br></span></b></span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><b style="mso-bidi-font-weight: normal;" data-mce-style="mso-bidi-font-weight: normal;"><span lang="EN-US" style="mso-ansi-language: EN-US;" data-mce-style="mso-ansi-language: EN-US;">References</span></b></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;"><span style="mso-spacerun: yes;" data-mce-style="mso-spacerun: yes;"><br></span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;"><span style="mso-spacerun: yes;" data-mce-style="mso-spacerun: yes;"> </span>[Nathwani <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">et al</i>., 2018] Nathwani, K., Vincent, E., and Illina, I. DNN uncertainty propagation using GMM-derived uncertainty features for noise robust ASR, <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">IEEE Signal Processing Letters</i>, 2018.</span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span lang="EN-US" style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;">[Nathwani <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">et al</i>., 2017] Nathwani, K., Vincent, E., and Illina, I. Consistent DNN uncertainty training and decoding for robust ASR, in <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">Proc.</i> <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">IEEE Automatic Speech Recognition and Understanding Workshop</i>, 2017.</span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt;" data-mce-style="font-size: 14pt;"><span lang="EN-US" style="line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="line-height: 107%; font-family: 'Times New Roman', serif;">[Nugraha <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">et al.,</i> 2016] Nugraha, A., Liutkus, A., Vincent E. Multichannel audio source separation with deep neural networks. </span><i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;"><span style="line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="line-height: 107%; font-family: 'Times New Roman', serif;">IEEE/ACM</span></i><span style="line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="line-height: 107%; font-family: 'Times New Roman', serif;"> <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">Transactions on Audio, Speech, and Language Processing</i>, 2016.</span></span></p><p class="MsoNormal" style="text-align: justify; margin: 0px;" data-mce-style="text-align: justify; margin: 0px;"><span style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;"><span style="mso-spacerun: yes;" data-mce-style="mso-spacerun: yes;"> </span>[Sheikh, 2016] Sheikh, I. Exploitation du contexte sémantique pour améliorer la reconnaissance des noms propres dans les documents audio diachroniques”, <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">These de doctorat en Informatique, Université de Lorraine,</i> 2016.</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;">[Sheikh <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">et al.,</i> 2016] Sheikh, I. Illina, I. Fohr, D. Linares, G. Learning word importance with the neural bag-of-words model, in Proc. ACL Representation Learning for NLP (Repl4NLP) Workshop, Aug 2016.</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;" data-mce-style="font-size: 14pt; line-height: 107%; font-family: 'Times New Roman', serif;">[Mikolov et al., 2013a] Mikolov, T. Chen, K., Corrado, G., and Dean, J. Efficient estimation of word representations in vector space, <i style="mso-bidi-font-style: normal;" data-mce-style="mso-bidi-font-style: normal;">CoRR</i>, vol. abs/1301.3781, 2013.</span></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><br></p><p class="MsoNormal" style="margin: 0px;" data-mce-style="margin: 0px;"><span lang="EN-US" style="font-size: 14pt;" data-mce-style="font-size: 14pt;"> </span></p><br></div><br><div>-- <br></div><div>Associate Professor <br>Lorraine University<br>LORIA-INRIA<br>office C147 <br>Building C <br>615 rue du Jardin Botanique<br>54600 Villers-les-Nancy Cedex<br>Tel:+ 33 3 54 95 84 90</div></div><br></div><div><br></div><div data-marker="__SIG_POST__">-- <br></div><div>Associate Professor <br>Lorraine University<br>LORIA-INRIA<br>office C147 <br>Building C <br>615 rue du Jardin Botanique<br>54600 Villers-les-Nancy Cedex<br>Tel:+ 33 3 54 95 84 90</div></div></body></html>