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<html><head>
<title>601.467/667 Introduction to Human Language Technology</title></head>
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<h1>601.467/667 Introduction to Human Language Technology</h2>
<hr>
<h2>Fall 2019</h2>
<b>Coordinator:</b> <a href="http://www.cs.jhu.edu/~phi/">Philipp Koehn</a> ([email protected])<br/>
<b>TAs:</b> Adi Renduchintala ([email protected]), Daniil Pakhomov ([email protected])<br/>
<b>Class:</b> Monday and Wednesdays 3:00-4:15pm, <a href="https://www.jhu.edu/maps-directions/campus-map/">Olin 305</a><br/>
<b>Office hours:</b> Coordinator: Hackerman 227, Wednesdays 12-1<br/>
<b>Office hours:</b> Adi Renduchintala: Olin 305, Wednesdays 4:15-6pm<br/>
<b>Office hours:</b> Daniil Pakhomov: Olin 305, Wednesdays 4:15-6pm<br/>
<b><a href="https://gradescope.com/">Gradescope</a></b> ☆
<b><a href="https://piazza.com/jhu">Piazza</a></b>
<h2>Assignments</h2>
<ol>
<li> <s> Kaldi speech recognition, presented in class September 16 </s>
<li><a href="assignments/HLT_HW1.pdf">Deep learning for speech</a>
<li><a href="assignments/HLT_HW2.pdf">Language Modelling with RNNs</a>
<li><a href="assignments/HLT_HW3.pdf">Sequence-to-Sequence Modelling</a>
<li><a href="assignments/HLT_HW4.pdf">Sequence Classification with Transfer Learning</a>
</ol>
<h2>Exam</h2>
There will be a mid-term and final exam.
The exam is closed book but you are allowed to take one sheet of paper with notes (on both sides).
The final exam takes place on Wednesday, December 11 at 6-9 PM.</br>
<a href="exam/final-example.pdf">Example questions for the final exam.</a>
<h2>Lectures</h2>
<table>
<tr style="font-weight: 900; font-size: 14pt;">
<td><b>Date</b></td>
<td><b>Topic</b></td>
<td><b>Instructor</b></td>
</tr>
<tr><td>Th Aug 29</td><td><a href="slides/lecture-introduction.pdf">Introduction</a></td><td><a href="http://www.cs.jhu.edu/~phi/">Koehn</a></td></tr>
<tr><td colspan="3" align="center" style="font-weight: 900; font-size: 14pt;">Speech</td></tr>
<tr><td>W Sep 4</td><td><a href="slides/hynek-hearing-and-speaking.pdf">Auditory system</a></td><td><a href="https://www.clsp.jhu.edu/faculty-pages/hynek/">Hermansky</a></td></tr>
<tr><td>M Sep 9</td><td><a href="slides/hynek-hearing-and-speaking2.pdf">Speech basics</a></td><td><a href="https://www.clsp.jhu.edu/faculty-pages/hynek/">Hermansky</a></td></tr>
<tr><td>W Sep 11</td><td><a href="slides/IMA-Math-Seminar.pdf">Classic speech recognition</a><a href="#footnote1"><sup>1</sup></a> (<a href="slides/2016-06-WS16-Tutorial.pdf">additional slides</a>)</td><td><a href="https://www.clsp.jhu.edu/faculty-pages/sanjeev/">Khudanpur</a></td></tr>
<tr><td>M Sep 16</td><td>Hands on: Kaldi</td><td><a href="https://www.clsp.jhu.edu/faculty-pages/sanjeev/">Khudanpur</a></td></tr>
<tr><td>W Sep 18</td><td><a href="slides/speaker-id.pdf">Speaker recognition</a></td><td><a href="https://www.clsp.jhu.edu/faculty/najim-dehak/">Dehak</a></td></tr>
<tr><td>M Sep 23</td><td><a href="slides/deep-learning-1.pdf">Deep learning I</a></td><td><a href="https://sites.google.com/view/shinjiwatanabe">Watanabe</a></td></tr>
<tr><td>W Sep 25</td><td><a href="slides/deep-learning-2.pdf">Deep learning II</a></td><td><a href="https://sites.google.com/view/shinjiwatanabe">Watanabe</a></td></tr>
<tr><td>M Sep 30</td><td>Signal processing <a href="https://doc.lagout.org/science/0_Computer%20Science/2_Algorithms/Spoken%20Language%20Processing_%20A%20Guide%20to%20Theory%2C%20Algorithm%2C%20and%20System%20Development%20%5BHuang%2C%20Acero%20%26%20Hon%202001-05-05%5D.pdf">(Chapter 6)</a></td><td><a href="https://www.clsp.jhu.edu/faculty-pages/sanjeev/">Khudanpur</a></td></tr>
<tr><td>W Oct 2</td><td><a href="slides/end-to-end-neural-asr.pdf">End-to-end neural speech recognition</a></td><td><a href="https://sites.google.com/view/shinjiwatanabe">Watanabe</a></td></tr>
<tr><td>M Oct 7</td><td>Hands on: Deep learning</td><td><a href="https://sites.google.com/view/shinjiwatanabe">Watanabe</a></td></tr>
<tr><td>W Oct 9</td><td>Midterm Exam</td><td>-</td></tr>
<tr><td colspan="3" align="center" style="font-weight: 900; font-size: 14pt;">Text</td></tr>
<tr><td>M Oct 14</td><td><a href="slides/language-modeling.pdf">Words and Language Models</a></td><td><a href="https://www.cs.jhu.edu/~yarowsky/">Yarowsky</a></td></tr>
<tr><td>W Oct 16</td><td>Morphology</td><td><a href="https://www.cs.jhu.edu/~yarowsky/">Yarowsky</a></td></tr>
<tr><td>M Oct 21</td><td><a href="slides/syntax.pdf">Syntax</a></td><td><a href="https://mjpost.github.io/">Post</a></td></tr>
<tr><td>W Oct 23</td><td><a href="slides/semantics.pdf">Semantics</a></td><td><a href="https://mjpost.github.io/">Post</a></td></tr>
<tr><td>M Oct 28</td><td><a href="slides/lecture-information-extraction.pdf">Information Extraction</a></td><td><a href="http://www.cs.jhu.edu/~phi/">Koehn</a></td></tr>
<tr><td>W Oct 30</td><td><a href="slides/machine-translation.pdf">Machine Translation</a></td><td><a href="http://cs.jhu.edu/~kevinduh/">Duh</a></td></tr>
<tr><td>M Nov 4</td><td><a href="slides/distributional-semantics.pdf">Distributional Semantics</a></td><td><a href="https://www.clsp.jhu.edu/faculty/joao-sedoc/">Sedoc</a></td></tr>
<tr><td>W Nov 6</td><td><a href="slides/digital-humanities-hlt.pdf">NLP for Digital Humanities</a></td><td><a href="http://www.logical-space.org/">Lippincott</a></td></tr>
<tr><td>M Nov 11</td><td><a href="slides/information-retrieval.pdf">Information Retrieval</a></td><td><a href="http://cs.jhu.edu/~kevinduh/">Duh</a></td></tr>
<tr><td>W Nov 13</td><td><a href="slides/question-answering.pdf">Question Answering</a></td><td><a href="http://cs.jhu.edu/~kevinduh/">Duh</a></td></tr>
<tr><td>M Nov 18</td><td><a href="slides/intro-hlt-conversational-agent.pdf">Dialog Systems</a></td><td><a href="https://www.clsp.jhu.edu/faculty/joao-sedoc/">Sedoc</a></td></tr>
<tr><td>W Nov 20</td><td><a href="slides/dredze-clinical-nlp.pdf">Clinical NLP</a></td><td><a href="https://www.cs.jhu.edu/~mdredze/">Dredze</a></td></tr>
<tr><td>M Dec 2</td><td><a href="slides/intro-hlt-ethics-lec.pdf">Ethical Problems</a></td><td><a href="https://www.clsp.jhu.edu/faculty/joao-sedoc/">Sedoc</a></td></tr>
<tr><td>W Dec 4</td><td><a href="slides/linzen_nn_interpretation_guest_lecture.pdf">Analyzing and Interpreting Neural Networks for NLP</a></td><td><a href="http://tallinzen.net/">Linzen</a></td></tr>
<tr><td>F Dec 6</td><td>Review session in Mergenthaler 111</td><td>Koehn</td></tr>
</table>
<a name="footnote1"><sup>1</sup></a>These slides present an incomplete picture of what will be discussed in class. Attentive listening is recommended for gaining maximal benefit.</br>
</body></html>