05 |
08/27 |
2.1.3.4 |
Perception and Masking |
06 |
08/30 |
2.2 |
Phonetics and Phonology |
07 |
09/01 |
2.3 - 2.5 |
Syntax and Semantics |
08 |
09/03 |
5.5, 9.3 |
Sampling |
09 |
09/08 |
5.6, 5.7 |
Resampling |
10 |
09/10 |
10.1 - 10.4 |
Acoustic Transducers |
11 |
09/13 |
5.4 |
Temporal Analysis |
12 |
09/15 |
5.1 - 5.3 |
Frequency Domain Analysis |
13 |
09/17 |
Lectures 1-11 |
Exam No. 1 |
|
14 |
09/20 |
6.4 - 6.5 |
Cepstral Analysis |
15 |
09/22 |
6.1 - 6.3 |
Linear Prediction |
16 |
09/24 |
6.5.3 |
LP-Based Representations |
17 |
09/27 |
6.5.3, 9.3.4 |
Spectral Normalization |
18 |
09/29 |
9.3.3 |
Differentiation |
19 |
10/01 |
9.3.4, 3.2.2 |
Principal Components |
10/04 |
02/22 |
9.3.4, 3.2.2 |
Linear Discriminant Analysis |
21 |
10/06 |
8.2.1 |
Dynamic Programming |
22 |
10/08 |
8.2.2, 8.2.3 |
Fundamentals of Markov Models |
23 |
10/11 |
8.2.4, 4.4.2 |
Parameter Estimation |
24 |
10/13 |
8.2.4 |
HMM Training |
25 |
10/15 |
4.4.3, 8.3 |
Continuous Mixture Densities |
26 |
10/20 |
8.4 |
Practical Issues |
27 |
10/22 |
4.5 |
Decision Trees |
28 |
10/25 |
Lectures 12 - 28 |
Exam No. 2 |
29 |
10/27 |
8.5 |
Limitations of HMMs |
30 |
10/29 |
11.1 |
Formal Language Theory |
31 |
11/01 |
11.2.1 |
Context Free Grammars |
32 |
11/03 |
11.2.2, 11.3 |
N-gram Models and Complexity |
33 |
11/05 |
11.4 |
Smoothing |
34 |
11/08 |
12.1 |
Basic Search Algorithms |
35 |
11/10 |
12.2 - 12.4 |
Time Synchronous Search |
36 |
11/12 |
12.5 - 13.6 |
Stack Decoding |
37 |
11/15 |
13.1.1 - 13.1.3 |
Lexical Trees |
38 |
11/17 |
13.1.4 - 13.1.6 |
Efficent Trees |
39 |
11/19 |
3.2.3, 9.6 |
Adaptation |
40 |
11/22 |
Lectures 29 - 37 |
Exam No. 3 |
41 |
11/29 |
4.3 |
Discriminative Training |
42 |
12/01 |
4.3.3, 9.8.1 |
Neural Networks |
43 |
12/03 |
N/A |
Evaluation Metrics and Common Evaluations |
46 |
12/07 |
Cumulative |
Final Exam (12 - 3 PM) |
Homework: