Händelser: Data- och informationsteknikhttp://www.chalmers.se/sv/om-chalmers/kalendariumAktuella händelser på Chalmers tekniska högskolaFri, 06 Apr 2018 12:03:45 +0200http://www.chalmers.se/sv/om-chalmers/kalendariumhttps://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Microwave-Road-seminarium-Space-and-Satellite_25apr2018.aspxhttps://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Microwave-Road-seminarium-Space-and-Satellite_25apr2018.aspxMicrowave Road seminarium: Space and Satellite<p>RUAG Space, Solhusgatan 11, Göteborg</p><p>​Sverige och framför allt Västsverige har många världsledande rymd- och satellitföretag. Lyssna på några av dem på denna Microwave Road Event. Välkomna!</p>​<br />Satellitkommunikation är just nu i en revolutionerande fas för att utveckla överkomligt bredband till alla världens hörn med ny avancerad mikrovågs- och antennteknik. Nya högtransportsatelliter (HTS) har 100-1000 gånger mer kapacitet än traditionella tv-sändningssatelliter. Det är betydligt lägre kostnader för bredband via satelliter och öppnar helt nya affärsmöjligheter i stora delar av världen där 4 miljarder människor fortfarande saknar bredbandsanslutning. Väder, fjärranalys, GPS och vetenskapliga satelliter kommer även fortsättningsvis vara viktiga för samhället. Sverige och framför allt Västsverige har många världsledande rymd- och satellitföretag. Lyssna på några av dem på detta Microwave Road Event 25 april 2018.<br /><br /><span class="text-normal page-content"><span><strong>Anmälan senast den 18 april</strong>, till <a href="mailto:mats.andersson@forsway.com">mats.andersson@forsway.com</a>.<span style="display:inline-block"></span></span><br /><br />PROGRAM<br />16.00–16.30 Registration and Coffee<br />16.30–16.50 <strong>Deborah Lygonis</strong>, Innovatum, “ESA Business Incubation Centre in Sweden”<br />16.50–17.10 <strong>Mats Andersson</strong>, Forsway, ”Smart integration of satellite and terrestrial infrastructure”<br />17.10–17.30 <strong>Jörgen Nilsson</strong>, RUAG Space, “Q- and V-band converters for high throughput<br />communication satellites”<br />17.30–18.00 Coffee break and Scholarship ceremony<br />18.00–18.20 <strong>Jakob Kallmér</strong>, Satcube, “Lightweight terminal using high throughput satellites anywhere”<br />18.20–18.40 <strong>Anders Emrich</strong>, Omnisys, ”Microwave and THz instruments in space”<br />18.40–19.00 <strong>Oleg Lupikov</strong>, Chalmers, “Digital beamforming focal plane arrays for space-borne passive<br />ocean remote sensing”<br />19.00–21.00 Beverage, food and continuation space and satellite discussions </span>https://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Seminarium-Richard-Sproat_18maj2018.aspxhttps://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Seminarium-Richard-Sproat_18maj2018.aspxNeural models of text normalization for speech applications<p>Palmstedtsalen, Chalmers kårhus, Chalmersplatsen 1, Johanneberg</p><p>​Speaker: Richard Sproat, Research Scientist at Google Research, New York</p>​(Joint work with Ke Wu, Hao Zhang, Kyle Gorman, Felix Stahlberg, Xiaochang Peng and Brian Roark).<br /><br /><span class="text-normal page-content"><strong>Abstract:</strong> Speech applications such as text-to-speech (TTS) or automatic speech recognition (ASR), must not only know how to read ordinary words, but must also know how to read numbers, abbreviations, measure expressions, times, dates, and a whole range of other constructions that one frequently finds in written texts. The problem of dealing with such material is called text normalization. The traditional approach to this problem, and the one currently used in Google’s deployed TTS and ASR systems, involves large hand-constructed grammars, which are costly to develop and tricky to maintain. It would be nice if one could simply train a system from text paired with its verbalization.<br /><br />I will present our work on applying neural sequence-to-sequence RNN models to the problem of text normalization. Given sufficient training data, such models can achieve very high accuracy, but also tend to produce the occasional error — reading “kB” as “hectare”, misreading a long number such as “3,281” — that would be problematic in a real application. The most powerful method we have found to correct such errors is to use finite-state over-generating covering grammars at decoding time to guide the RNN away from “silly” readings: Such covering grammars can be learned from a very small amount of annotated data. The resulting system is thus a hybrid system, rather than a purely neural one, a purely neural approach being apparently impossible at present.<br /><br /><strong>Brief bio:</strong> Richard Sproat is a Research Scientist at Google Research, New York. From 2009-2012 he was a professor at the Center for Spoken Language Understanding at the Oregon Health and Science University. Prior to going to OHSU, he was a professor in the departments of Linguistics and Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He was also a full-time faculty member at the Beckman Institute. He still holds adjunct positions in Linguistics and ECE at UIUC. <br />Before joining the faculty at UIUC he worked in the Information Systems and Analysis Research Department headed by Ken Church at AT&amp;T Labs --- Research where he worked on Speech and Text Data Mining: extracting potentially useful information from large speech or text databases using a combination of speech/NLP technology and data mining techniques.<br />Before joining Ken's department he worked in the Human/Computer Interaction Research Department headed by Candy Kamm. His most recent project in that department was WordsEye, an automatic text-to-scene conversion system. The WordsEye technology is now being developed at Semantic Light, LLC.<br /><a href="https://research.google.com/pubs/RichardSproat.html">https://research.google.com/pubs/RichardSproat.html</a></span>https://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Swedish-Symposium-on-Deep-Learning.aspxhttps://www.chalmers.se/sv/styrkeomraden/ikt/kalendarium/Sidor/Swedish-Symposium-on-Deep-Learning.aspxSwedish Symposium on Deep Learning 2018<p>Wallenberg Conference Center, Medicinaregatan 20, Gothenburg</p><p>​The 2nd Swedish Symposium on Deep Learning will be held at Chalmers University of Technology, 4-5 September, 2018.</p>​ <br /><span><br />The premier event in Sweden bringing together top researchers in Deep Learning across academia and industry. This year there will be thematic sessions on Vision, Natural Language Technologies and Health Engineering, three of the most high impact areas for Deep Learning today.<br /><br /><strong>Keynote Speakers:</strong><br /><ul><li><a href="http://www.cs.cmu.edu/~cdyer/index.html" target="_blank">Chris Dyer</a>, Carnegie Mellon University (confirmed) </li> <li>Trevor Darrell, U.C. Berkeley (to be confirmed) </li> <li>David Nistér, Vice-President, NVIDIA self-driving cars (Sweden) (to be confirmed)</li> <li><a href="http://www.csc.kth.se/~azizpour/" target="_blank">Hossein Azizpour</a>, KTH Royal Institute of Technology (confirmed)</li></ul> <p><br /></p> <p>The programme will be continuously updated and announced.<br /></p> </span>https://www.chalmers.se/sv/om-chalmers/kalendarium/Sidor/Chalmers-Hallbarhetsdag2018.aspxhttps://www.chalmers.se/sv/om-chalmers/kalendarium/Sidor/Chalmers-Hallbarhetsdag2018.aspxChalmers Hållbarhetsdag 2018<p>TBA</p><p>​Chalmers Hållbarhetsdag är tillbaka – tisdag 23 oktober 2018. Temat för i år är God hälsa och välbefinnande.</p>​<br />Mer information kommer, håll dig uppdaterad genom eventets webbsida: <a href="/sv/om-chalmers/miljo-och-hallbar-utveckling/hallbarhetsdagen2018/Sidor/default.aspx">Chalmers Hållbarhetsdag 2018</a>.<br /><br />Markera dagen i din kalender!<span class="text-normal page-content"></span><br />