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 <h2 id="About-the-CCRMA-Workshop-on-Music-Information-Retrieval">About the CCRMA Workshop on Music Information Retrieval<a class="anchor-link" href="#About-the-CCRMA-Workshop-on-Music-Information-Retrieval">&#194;&#182;</a></h2>
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+<p><em>"You guys put together a really fantastic workshop."</em></p>
+<p><em>"I really enjoyed the workshop. It was very well executed and exceeded my expectations in the scope of material covered."</em></p>
+<p><em>"well planned and thoughtful."</em></p>
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 <p>The MIR workshop teaches the underlying ideas, approaches, technologies, and practical design of intelligent audio systems using MIR algorithms. It lasts five full days, Monday through Friday. It was founded by <a href="https://www.linkedin.com/in/jayleboeuf">Jay LeBoeuf</a> (Real Industry, CCRMA consulting professor) in 2008.</p>
-<p>The workshop is intended for students, researchers, and industry audio engineers who are unfamiliar with the field of music information retrieval (MIR). We demonstrate the technologies enabled by signal processing and machine learning. Lectures cover topics such as low-level feature extraction, higher-level features such as chord estimations, audio similarity clustering, search and retrieval, and design and evaluation of classification systems. Our goal is to make these interdisciplinary technologies and complex algorithms approachable.</p>
+<p>The workshop is intended for students, researchers, and industry audio engineers who are unfamiliar with the field of music information retrieval (MIR). We demonstrate the technologies enabled by signal processing and machine learning. Lectures cover topics such as low-level feature extraction, higher-level features such as chord estimations, audio similarity clustering, search and retrieval, music synchronization, signal decomposition, rhythm and tempo, and design and evaluation of classification systems. Our goal is to make these interdisciplinary technologies and complex algorithms approachable.</p>
 <p>Knowledge of basic digital audio principles is recommended.  Experience with a scripting language such as Python or Matlab is desired. Students are encouraged to bring their own audio source material for course labs and demonstrations.</p>
 <p>The workshop consists of half-day lectures, half-day supervised lab sessions, demonstrations, and discussions. Labs allow students to design basic "intelligent audio systems" leveraging existing MIR toolboxes, programming environments, and applications. Labs include creation and evaluation of basic instrument recognition, transcription, and real-time audio analysis systems.</p>
 

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     "## About the CCRMA Workshop on Music Information Retrieval"
    ]
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+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*\"You guys put together a really fantastic workshop.\"*\n",
+    "\n",
+    "*\"I really enjoyed the workshop. It was very well executed and exceeded my expectations in the scope of material covered.\"*\n",
+    "\n",
+    "*\"well planned and thoughtful.\"*"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "The MIR workshop teaches the underlying ideas, approaches, technologies, and practical design of intelligent audio systems using MIR algorithms. It lasts five full days, Monday through Friday. It was founded by [Jay LeBoeuf](https://www.linkedin.com/in/jayleboeuf) (Real Industry, CCRMA consulting professor) in 2008.\n",
     "\n",
-    "The workshop is intended for students, researchers, and industry audio engineers who are unfamiliar with the field of music information retrieval (MIR). We demonstrate the technologies enabled by signal processing and machine learning. Lectures cover topics such as low-level feature extraction, higher-level features such as chord estimations, audio similarity clustering, search and retrieval, and design and evaluation of classification systems. Our goal is to make these interdisciplinary technologies and complex algorithms approachable.\n",
+    "The workshop is intended for students, researchers, and industry audio engineers who are unfamiliar with the field of music information retrieval (MIR). We demonstrate the technologies enabled by signal processing and machine learning. Lectures cover topics such as low-level feature extraction, higher-level features such as chord estimations, audio similarity clustering, search and retrieval, music synchronization, signal decomposition, rhythm and tempo, and design and evaluation of classification systems. Our goal is to make these interdisciplinary technologies and complex algorithms approachable.\n",
     "\n",
     "Knowledge of basic digital audio principles is recommended.  Experience with a scripting language such as Python or Matlab is desired. Students are encouraged to bring their own audio source material for course labs and demonstrations.\n",
     "\n",