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Duration modeling for speech Duration modeling for speech recognitionrecognition

Presented for BBN

Dr. Andrey Nikiforov

Department of Applied Mathematics and Statistics

State University of New York at Stony Brook

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Additional topics

Computational and modeling issues improving the performance of speech recognition algorithms

Partial classification techniques Tree-dependence covariance models in HMM Fast search and computations for codebooks Interpolation for acoustic space

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State duration in HMM

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Duration distributions

Duration probability density functions

Time

Exponential

Raleigh

Weibull

Normal

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From …

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… to

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Progressive model

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Time calculation

BA

t t+1

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Time calculation (continued)

BA

t t+1

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Probability calculations: from …

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…to

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Hazard function

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Hazard function estimation

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“Nonparametric estimate”

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“Trajectories”

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State duration correction

(Fant et al., 1991)

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Word duration

0.0

2.7

5.3

8.0

30.0 41.7 53.3 65.0

Word duration distribution

Word_length__frames_

Count

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State duration correction

0.0

2.7

5.3

8.0

0.0 0.1 0.1 0.1

State duration distribution

C4

Count

0.0

2.7

5.3

8.0

0.0 0.1 0.1 0.1

State duration distribution

C5

Count

0.0

4.7

9.3

14.0

2.8 3.3 3.7 4.2

State duration distribution

C4

Count

0.0

4.0

8.0

12.0

2.5 3.5 4.5 5.5

State duration distribution

C5

Count

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State duration correction (continued)

0.0

2.7

5.3

8.0

0.1 0.1 0.1 0.1

State duration distribution

C6

Count

0.0

3.3

6.7

10.0

0.0 0.1 0.1 0.2

State duration distribution

C7

Count

0.0

5.0

10.0

15.0

2.5 3.7 4.8 6.0

State duration distribution

C6

Count

0.0

6.7

13.3

20.0

2.0 4.7 7.3 10.0

State duration distribution

C7

Count

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Conclusions

• Representation of duration distribution via the hazard function is simple, effective and comfortable for programming

• Speech recognition errors dropped by 20-25% in different tasks

•  Pure time spent in Viterbi search or full probability calculation increased in average by 20% compared to the conventional HMM (almost completely compensated by the reduction of computations due to more adequate modeling)

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Partial classification techniques for speech recognition

Helps to create structure in speech HMMs

Useful in codebook(s) estimation

Initial estimates for HMMs and codebooks

More accurate estimates