:Units Paper
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(Difference between revisions)
| Line 152: | Line 152: | ||
With >= 1 occurances (2699) | With >= 1 occurances (2699) | ||
| + | === LM_PENALTY = -3 === | ||
| + | DETAILED OVERALL REPORT FOR THE SYSTEM: test/config16/test0/accuracy/out.nosil.trn | ||
| + | |||
| + | SENTENCE RECOGNITION PERFORMANCE | ||
| + | |||
| + | sentences 500 | ||
| + | with errors 87.0% ( 435) | ||
| + | |||
| + | with substitions 72.6% ( 363) | ||
| + | with deletions 40.6% ( 203) | ||
| + | with insertions 56.4% ( 282) | ||
| + | |||
| + | |||
| + | WORD RECOGNITION PERFORMANCE | ||
| + | |||
| + | Percent Total Error = 88.9% (4535) | ||
| + | |||
| + | Percent Correct = 25.4% (1298) | ||
| + | |||
| + | Percent Substitution = 63.0% (3215) | ||
| + | Percent Deletions = 11.5% ( 588) | ||
| + | Percent Insertions = 14.4% ( 732) | ||
| + | Percent Word Accuracy = 11.1% | ||
| + | |||
| + | |||
| + | Ref. words = (5101) | ||
| + | Hyp. words = (5245) | ||
| + | Aligned words = (5833) | ||
| + | |||
| + | CONFUSION PAIRS Total (2671) | ||
| + | With >= 1 occurances (2671) | ||
| + | |||
| + | '''Clearly there is something wrong with the monophone model - a triunit gaussian model seems about even with monophone gaussian model - should be better by about 10% WER, I think.''' | ||
== Monophone tests == | == Monophone tests == | ||
| Line 184: | Line 217: | ||
Hyp. words = (4047) | Hyp. words = (4047) | ||
Aligned words = (5387) | Aligned words = (5387) | ||
| + | |||
| + | |||
[[Category:Fisher Experiments]] | [[Category:Fisher Experiments]] | ||
Revision as of 22:21, 11 April 2009
Contents |
Outline
- Intro
- Unit Selection
- Mistake instance
- Unit
- Replacement
- Multwords
- Baseline Description
- Vocab: single most frequent pronunciation from a multi-pronunciation dictionary (better than multi-pronunciation)
- Results
- what to emphasize? Ideally, units+DTs will beat just DTs for every number of components. Even if we cannot grow the components until improvement bottoms out, at least there will be a trend.
- Conclusion
- Future work: consider context during unit selection (right now the unit is context-free - the same unit appearing in all contexts where replacements took place).
Tests for units paper
| compPer: | units: | monophone states | Mix: | totalComp: | WER | Test WER | Important |
|---|---|---|---|---|---|---|---|
| 512 | 1 | 503 | 256k | TR | |||
| 256 | 1 | 1000 | 256k | TR | |||
| 64 | 1 | 3854 | 256k | 49.3 | |||
| 64 | 2 | 2000 | 256k | ? | |||
| 32 | 4 | 2000 | 256k | ? | |||
| 32 | 2 | 4000 | 256k | ? | |||
| alternatively | |||||||
| 256 | 48 | 137 | 503 | 127971 | 53.0 | ||
| 128 | 48 | 137 | 1033 | 131185 | 50.9 | ||
| 32 | 48 | 137 | 3845 | 122907 | 51.4 | ||
| 64 | 112 | 615 | 2024 | ~128k | TR | ||
| 16 | 4 | 2000 | 128k | ? | |||
| 16 | 112 | 615 | 4000 | 128k | ? |
The units make it worse
with LM_PENALTY=0
DETAILED OVERALL REPORT FOR THE SYSTEM: test/config16/test0/accuracy/out.nosil.trn
SENTENCE RECOGNITION PERFORMANCE
sentences 500
with errors 89.2% ( 446)
with substitions 72.4% ( 362)
with deletions 26.2% ( 131)
with insertions 74.4% ( 372)
WORD RECOGNITION PERFORMANCE
Percent Total Error = 99.1% (5107)
Percent Correct = 28.6% (1476)
Percent Substitution = 66.2% (3411)
Percent Deletions = 5.1% ( 265)
Percent Insertions = 27.8% (1431)
Percent Word Accuracy = 0.9%
Ref. words = (5152)
Hyp. words = (6318)
Aligned words = (6583)
CONFUSION PAIRS Total (2790)
With >= 1 occurances (2790)
with LM_PENALTY=-1
test2kUtt/config16Disaster/test0/accuracy/out.nosil.trn.dtl DETAILED OVERALL REPORT FOR THE SYSTEM: test2kUtt/config16/test0/accuracy/out.nosil.trn SENTENCE RECOGNITION PERFORMANCE sentences 500 with errors 88.2% ( 441) with substitions 72.8% ( 364) with deletions 32.8% ( 164) with insertions 68.6% ( 343) WORD RECOGNITION PERFORMANCE Percent Total Error = 94.6% (4857) Percent Correct = 27.6% (1417) Percent Substitution = 65.4% (3358) Percent Deletions = 7.0% ( 357) Percent Insertions = 22.3% (1142) Percent Word Accuracy = 5.4% Ref. words = (5132) Hyp. words = (5917) Aligned words = (6274)
LM_PENALTY = -2
DETAILED OVERALL REPORT FOR THE SYSTEM: test/config16/test0/accuracy/out.nosil.trn
SENTENCE RECOGNITION PERFORMANCE
sentences 500
with errors 87.2% ( 436)
with substitions 72.8% ( 364)
with deletions 38.8% ( 194)
with insertions 62.8% ( 314)
WORD RECOGNITION PERFORMANCE
Percent Total Error = 91.4% (4674)
Percent Correct = 26.9% (1374)
Percent Substitution = 64.0% (3271)
Percent Deletions = 9.2% ( 468)
Percent Insertions = 18.3% ( 935)
Percent Word Accuracy = 8.6%
Ref. words = (5113)
Hyp. words = (5580)
Aligned words = (6048)
CONFUSION PAIRS Total (2699)
With >= 1 occurances (2699)
LM_PENALTY = -3
DETAILED OVERALL REPORT FOR THE SYSTEM: test/config16/test0/accuracy/out.nosil.trn
SENTENCE RECOGNITION PERFORMANCE
sentences 500
with errors 87.0% ( 435)
with substitions 72.6% ( 363)
with deletions 40.6% ( 203)
with insertions 56.4% ( 282)
WORD RECOGNITION PERFORMANCE
Percent Total Error = 88.9% (4535)
Percent Correct = 25.4% (1298)
Percent Substitution = 63.0% (3215)
Percent Deletions = 11.5% ( 588)
Percent Insertions = 14.4% ( 732)
Percent Word Accuracy = 11.1%
Ref. words = (5101)
Hyp. words = (5245)
Aligned words = (5833)
CONFUSION PAIRS Total (2671)
With >= 1 occurances (2671)
Clearly there is something wrong with the monophone model - a triunit gaussian model seems about even with monophone gaussian model - should be better by about 10% WER, I think.
Monophone tests
Trying to track down where the error is coming from:
Standard monophone converged once WER 86.8:
DETAILED OVERALL REPORT FOR THE SYSTEM: trTest/config19/test0/accuracy/out.nosil.trn SENTENCE RECOGNITION PERFORMANCE sentences 500 with errors 83.4% ( 417) with substitions 69.4% ( 347) with deletions 52.8% ( 264) with insertions 33.6% ( 168) WORD RECOGNITION PERFORMANCE Percent Total Error = 86.8% (4426) Percent Correct = 18.9% ( 961) Percent Substitution = 54.9% (2796) Percent Deletions = 26.3% (1340) Percent Insertions = 5.7% ( 290) Percent Word Accuracy = 13.2% Ref. words = (5097) Hyp. words = (4047) Aligned words = (5387)
