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so hi everybody thanks a lot for inviting me to this itamp;#39;s been really fun so far weamp;#39;ve had a bunch of really interesting science talks about human speech processing and I guess weamp;#39;re going to go back to Machine speech processing for a little while so this talk is about representations of spoken words and how we can learn them from data and so this is something that Iamp;#39;ve started to work on recently with a bunch of collaborators both at TTI and outside of TTI and itamp;#39;s been a really fun playground to play on so Iamp;#39;ll show you a little bit of what weamp;#39;ve what weamp;#39;ve done so far so anybody who is in natural language processing or text processing knows word embeddings in the sense of textual word embeddings so word embeddings have pretty much taken NLP by storm theyamp;#39;re ubiquitous and almost any NLP application from machine translation to parsing to part of speech tagging and so on and the idea in textual word embeddings is
