Added Rabiner's classic paper

edward · Jul 22, 2008 · 5a47a5b · 5a47a5b
1 parent 982ea16
commit 5a47a5b
Show file tree

Hide file tree

Showing 2 changed files with 5 additions and 1 deletion.
diff --git a/README b/README
@@ -25,4 +25,8 @@ There are three canonical problems associated with HMM:
 
   Given the parameters of the model, find the most likely sequence of hidden states that could have generated a given output sequence. This problem is solved by the Viterbi algorithm.
 
-  Given an output sequence or a set of such sequences, find the most likely set of state transition and output probabilities. In other words, discover the parameters of the HMM given a dataset of sequences. This problem is solved by the Baum-Welch algorithm.
+  Given an output sequence or a set of such sequences, find the most likely set of state transition and output probabilities. In other words, discover the parameters of the HMM given a dataset of sequences. This problem is solved by the Baum-Welch algorithm.
+
+Papers
+
+  I’ll start to put together a collection of papers (and hopefully not cry when I get sent notices to remove them), but for the time being, the classic is Rabiner’s “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition”. It’s a beast, but an awesome one at that.
diff --git a/papers/tutorial on hmm and applications.pdf b/papers/tutorial on hmm and applications.pdf