1 Best Practices for Voice Authentication Charles R. Jankowski Jr., Ph. D. SpeechTek West 2007 February 21, 2007.

1

Best Practices for Voice Authentication

Charles R. Jankowski Jr., Ph. D.SpeechTek West 2007February 21, 2007

2

Design for Voice Authentication

Dialog design is the single most critical aspect of voice authentication performance

3

Make Verifier SECUREMake Verifier SECURE

Make Verifier EASY to useMake Verifier EASY to use

Verifier Dialog and Application Design

4

Verifier Performance Measures

Automation Rate– Percentage of repeat true speakers automated by system– 100 – False Reject Rate

• Security Rate– 100 – False Accept Rate

5

Baseline Performance

Automation Rate

94% 99%93%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Very High High MediumSecurity Level

6

Existing ID/Authentication

SSN/Account#

PIN

7

Enrollment

SSN/Account#

PIN

1-9

1-9

1-9

KV selection

Used by Verifier Optional

8

Verification

SSN/Account#

1-9

1-9

KV

Used by Verifier Optional

9

Summary of design takeaways

1. Maintain consistency between enrollment and verification dialogs

2. Collect enough data during enrollment and verification

3. Use variable length verification

4. Use knowledge verification

5. Use speaker adaptation

10

1. Maintain consistency between enrollment and verification

SSN/Account#

Authentication

1-9

1-9

1-9

KV selection

SSN/Account#

1-9

1-9

KV

• Only using 1-9 for voiceprint creation and checking

• Could also use account number, phone number, etc…

11

Choice of Verification Utterance

• Why use identity claim?– One shorter dialog step– 80% of users claim and verify in one step

• Why use common?– Many users do not like to speak their identity claim in public

• Identity theft• Allow option to touch-tone identity claim

– Multiple options for Identification• Enrollment very complex and long

– Common utterance performance more predictable• Out-of-the-box performance better understood• ID claim may vary in length

– Evaluating performance with identity claim more complex• Impostors MUST speak same text as enrollee• Identity claim -> Need live impostors

12

2. Collect enough data during enrollment and verification

SSN/Account#

Authentication

1-9

1-9

1-9

KV selection

SSN/Account#

1-9

1-9

KV

• 3 Enrollment utterances instead of 2: 1-3% lower automation

• 1 Verification utterance instead of 2: 1-3% lower automation

13

3. Use variable length verification

SSN/Account#

Authentication

1-9

1-9

1-9

KV selection

SSN/Account#

1-9 80%

1-9 10%

• Same verification performance as with 2 required utterances

14

4. Use knowledge verification

SSN/Account#

Authentication

1-9

1-9

1-9

KV selection

SSN/Account#

1-9

1-9

80%

10%

KV 10%

• Examples: PIN, Secret Date

• Verifier not turned on

• Increases Automation

• Increases Effectiveness of Adaptation

15

5. Use speaker adaptation

SSN/Account#

Authentication

1-9

1-9

1-9

KV selection

SSN/Account#

1-9

1-9

KV

16

Speaker Verification Performance

• Speaker Adaptation– Online: Score very well, adapt and get even better

– Manual: Unsure, backoff to knowledge, adapt if knowledge passes

• Cross-channel

Digit Voiceprints

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

0 2 4 6 8 10 12

Number of adaptation calls

Fa

lse

re

jec

t ra

te (

FR

)

Online all data

Online same channel only

Manual all data

Manual same channel only

17

Thank You!

• www.nuance.com