Biometrics & Security Tutorial 10. 1. (a) Understand the difference between voice biometrics and speech recognition? (P12: 10). What is text-dependent.

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Presentation transcript:

Biometrics & Security Tutorial 10

1. (a) Understand the difference between voice biometrics and speech recognition? (P12: 10). What is text-dependent and text- independent speaker ID? (P12:11).

1 (b) Generally speaking, on-line signature recognition is more accurate than off-line. Can you give some reasons? (P11:5)

Online signature has more features (shape and time element) Not only physical feature, but also behavioral feature

1 (c) What are the advantages and disadvantages of voice and signature biometrics, respectively? (P11: 31; P12: 24)

1 (d) Show both global and local features for on-line signature verification. (P11: 19)

The total elapsed time and signature size ( bounding box ) are Global Features; All of the others are Local Features; The average speed for an entire signature is Global Feature; The speed at each point is Local Feature

2. Features used by voice identification include cadence, frequency, pitch & tone of an individual’s voice. In P12:12 the models for two speakers saying the same vowel are given. Please try to define a minimum feature set to divide the two models. (frequency, magnitude)

Different frequency Different magnitude

3. Directional frontier (DF) is a directional grouping of the contour pixels. In P11:22, there is an example of DF curve characterization. Please give the corresponding feature set. (end points, angle (major orientation), skew (line of best-fit), via points, spline curve, middle point, number of points)

4. Please write down your signature. Based on the definitions given in P11:10-12, please find the following features: Upper/lower envelop, vertical /horizontal projection, geometric and topological features.

Bars Loops