1. Sphinx 3.X (X=4)
Four-Layer Categorization Scheme of Fast GMM Computation Techniques in
Large Vocabulary Continuous Speech Recognition Systems
Arthur Chan, Jahanzeb Sherwani,
Ravishankar Mosur and Alex Rudnicky
Computer Science Department,
Carnegie Mellon University
Sphinx 3.X (X=4)
Sphinx: -speaker-independent large vocabulary speech recognition system
-open source under Berkeley-style license: one can distribute, modify and use it freely
Sphinx 3.X: Reengineering of Sphinx 3 to create a real-time large vocabulary speech recognizer
-S3.3: Tree lexicon, Histogram Pruning and Live-mode decoder (R. Mosur 1999)
-S3.4 (released Jul 04): Fast GMM Computation , Phoneme look-ahead. (A. Chan 2004, this paper.)
-S3.5 (will soon release): MLLR-based Speaker Adaptation , live-mode APIs, alignment, phoneme recognition, lattice rescoring, best path search in lattice.
4-Level of GMM Computation
GMMs
Frames
Gaussians
Feature Component
Gaussian-level
-VQ-based Gaussian Selection (Bochierri 93)
-SVQ-base Gaussian Selection (Mosur 99)
Feature-level
-Sub vector quantization or SDCHMM method
(Mosur 97 Mak 97)
-LDA, PCA
Frame-Level:
-Discount alternative frames
-Down Sampling (Wycesna 95)
GMM-Level:
-Only compute important GMM. (e.g. w high CI score)
-CI-GMM Selection (Lee 01)
Sphinx 3.4: Fast GMM Computation
Experiment Results
Our approach:
-Divide GMM computation in 4 levels
-Implement representative techniques in each level
-Inspired by 4-level state tying (Sagayama 95)
Observation: In each level, full computation can be approximated by computing only parts of the components.
Advantages: Provide a general framework of understanding fast GMM computation
Experiment Summary:
1, CI-based GMM Selection seems to most effective.
2, Many Gaussian-level techniques seems to have too much overhead.
Algorithm
WER
Total
GMM
Srch
Ovhd BL
18.65
6.9
5.85
0.85 -
Down Sampling
19.10
4.35
3.99
0.96
CIGMMS
18.82
3.25
1.18
2.06
Gaussian
Selection
18.95
3.95
2.84
0.89
0.22
SVQ
18.69
4.20
2.04
0.98
1.08
Note: Results combined with pruning can be found in the paper.