Always in the quest for better performance, I decided to fiddle around with the various audio settings available for speech recognition and see if any of them yielded better results.
Base system (unless noted otherwise):
Core i5 760 no overclock, 4 gig ram, Gigabyte GA-P55-USB3 motherboard
Win 7
Dragon NaturallySpeaking 11.0
Andrea PureAudio USB soundpod external soundcard
VXI microphone
Methodology:
A new user with only the initial training
Same text: National Geographic magazine November 2005 page 1: Who Knew?
Change a variable
Compare number of misrecognitions on each variable change
If uncertain, repeat
Raw data:
# of misrecognitions
Nc= noise cancellation
Nonc= no noice cancellation
30 Micro boost
NC
|
25
|
Nonc
|
30
|
Nc vxi
|
21
|
Nc+ LB
|
32+
|
0 boost
Regular
|
41
|
A NC
|
40
|
Vxi
|
23
|
NC Vxi
|
21
|
Vxi dif Lmodel
|
18
|
+NC
|
29
|
Andrea
|
27
|
Vxi
|
14
|
Vxi Nc
|
15
|
Other text
Vxi
|
28
|
Vxi nc
|
26
|
Vxi dif Lmodel
|
22
|
Vxi dif Lmodel NC
|
23
|
VXI Within a virtual machine
Out
|
15
|
VM
|
15
|
Vxi dif Lmodel 10db boost
Vxi
|
24
|
Vxi Nc
|
21
|
vxi
Dragon trained
|
10
|
Win7 Speech recognition no training
|
40
|
Acoustic adaptation
Pre optimized
|
13
|
Post
|
44
|
Post round#2
|
14
|
Conclusions:
- A sound pod is better than integrated sound
- Microphone boost, software noise cancellation and surround settings are best left alone
- The VXI microphone is way better than my old Andrea NC8
- From the get go, Dragon NaturallySpeaking is better than Windows speech recognition
- There is no impact on using it within a virtual machine
- Training the software and correcting misrecognitions works, though I've had mixed results with the acoustic adaptation feature
- Just from personal experience, there are limits to training: some misrecognitions will always remain
0 comments:
Post a Comment