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Chapter 15 Probabilistic Reasoning over Time

Chapter 15 Probabilistic Reasoning over Time. Chapter 15, Sections 1-5 Outline. Time and uncertainty Inference: ltering, prediction, smoothing Hidden Markov models Kalman lters (a brief mention) Dynamic Bayesian networks Particle ltering. Time and uncertainty.

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Chapter 15 Probabilistic Reasoning over Time

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  1. Chapter 15Probabilistic Reasoning over Time

  2. Chapter 15, Sections 1-5Outline • Time and uncertainty • Inference: ltering, prediction, smoothing • Hidden Markov models • Kalman lters (a brief mention) • Dynamic Bayesian networks • Particle ltering

  3. Time and uncertainty • The world changes; we need to track and predict it • Diabetes management vs vehicle diagnosis • Basic idea: copy state and evidence variables for each time step

  4. Markov processes (Markov chains)

  5. Example

  6. Inference tasks

  7. Filtering

  8. Filtering example

  9. Smoothing

  10. Smoothing example

  11. Most likely explanation

  12. Viterbi example

  13. Hidden Markov models

  14. Country dance algorithm

  15. Country dance algorithm

  16. Country dance algorithm

  17. Country dance algorithm

  18. Country dance algorithm

  19. Country dance algorithm

  20. Country dance algorithm

  21. Country dance algorithm

  22. Country dance algorithm

  23. Country dance algorithm

  24. Kalman lters

  25. Updating Gaussian distributions

  26. Simple 1-D example

  27. General Kalman update

  28. 2-D tracking example: ltering

  29. 2-D tracking example: smoothing

  30. Where it breaks

  31. Dynamic Bayesian networks

  32. DBNs vs. HMMs

  33. DBNs vs Kalman lters

  34. Exact inference in DBNs

  35. Likelihood weighting for DBNs

  36. Particle ltering

  37. Particle ltering contd.

  38. Particle ltering performance

  39. Chapter 15, Sections 1-5 Summary

  40. Chapter 15, Section 6Outline • Speech as probabilistic inference • Speech sounds • Word pronunciation • Word sequences

  41. Speech as probabilistic inference

  42. Phones

  43. Speech sounds

  44. Phone models

  45. Phone model example

  46. Word pronunciation models

  47. Isolated words

  48. Continuous speech

  49. Language model

  50. Combined HMM

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