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Jim O'Regan
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Presentation given on June 15, 2022 at Fonetik in Stockholm.
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Continued Fine-tuning as Single Speaker Adaptation
1.
Continued Fine-tuning as
Single Speaker Adaptation Jim O’Regan
2.
Trend 2 Pretrained base model (Usually
using self-supervised learning on large amounts of data) Fine-tuned for a particular task (Usually using a much smaller amount of task-specific data)
3.
Two questions 3
4.
Two questions 4 • Does
it work? • How much data do I need?
5.
Does it work? 2019-04-09
5
6.
Does it work? 2019-04-09
6
7.
Does it work? 2019-04-09
7 It worked for me, multiple times, for multiple speakers
8.
Does it work? 2019-04-09
8 It worked for me, multiple times, for multiple speakers YMMV
9.
Does it work? 2019-04-09
9 It worked for me, multiple times, for multiple speakers YMMV (Your Mileage May Vary)
10.
“How much data
do I need?” 2019-04-09 10
11.
“How much data
do I need?” 2019-04-09 11 “As much as possible”
12.
“How much data
do I need?” 2019-04-09 12 “As much as possible” (Thanks for nothing)
13.
Delicious numbers 2019-04-09 13 Time
WER Time WER Time WER 5 5.34 45 3.2 85 2.67 10 5.31 50 2.89 90 2.6 15 5.3 55 2.91 95 2.39 20 3.35 60 2.85 100 2.54 25 3.36 65 2.69 105 2.51 30 3.36 70 2.94 110 2.59 35 3.22 75 2.59 115 2.71 40 3.13 80 2.77 120 2.57
14.
But I’m allergic
to numbers! 14
15.
Increased early stopping 15 Minutes
300 1000 WER Time (sec) WER Time (sec) 5 5.34 10912.7 4.11 42180.1 10 5.31 10540.1 4.08 32147.6 15 5.30 8515.5 3.72 28848.0 20 3.35 16195.9 3.49 27926.7 25 3.36 14774.0 3.43 26710.9 30 3.36 14082.0 3.34 25955.9
16.
Early stopping: 300
vs 1000 epochs 16 Minutes 300 1000 WER Time (hours) WER Time (hours) 5 5.34 3.03 4.11 11.71 10 5.31 2.93 4.08 8.93 15 5.30 2.37 3.72 8.01 20 3.35 4.5 3.49 7.76 25 3.36 4.1 3.43 7.42 30 3.36 3.91 3.34 7.21
17.
17
18.
Higher resource (hours
of data) 18 Time WER Time WER 2 2.57 10 1.38 4 1.47 12 1.22 6 1.66 14 1.13 8 1.47 16 1.03
19.
19
20.
Accented speech 20 Time WER
Time WER 5 5.77 35 3.65 10 5.77 40 3.65 15 5.58 45 2.50 20 4.62 50 3.65 25 3.85 55 2.69 30 4.62 60 3.27
21.
21
22.
Conclusions 22 • Continued fine-tuning
works as a speaker adaptation method • More data is always better, but aim for at least 20-25 minutes
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