Speech recognition using neural networks - Chapter 7 pdf
Speech recognition using neural networks - Chapter 7 pdf
... training of a speech recognizer?”
7. 5. Summary
143
7. 5. Summary
In this chapter we have seen that good word recognition accuracy can be achieved using
neural networks that have been trained as speech ... 4 5
epochs
3600 train, 390 test. (Aug24)
FFT-16
FFT-32 (with deltas)
PLP-26 (with deltas)
LDA-16 (derived from FFT-32)
7. 3. Frame Level Training
121
7. 3.4.1. Learning Ra...
Speech recognition using neural networks - Chapter 1 pot
... volumes, and so on,
x
Speech Recognition using Neural Networks
Joe Tebelskis
May 1995
CMU-CS-9 5-1 42
School of Computer Science
Carnegie Mellon University
Pittsburgh, Pennsylvania 1521 3-3 890
Submitted ... that neural networks can indeed form the basis for a general pur-
pose speech recognition system, and that neural networks offer some clear advantages over
conve...
Speech recognition using neural networks - Chapter 2 docx
... /ts/
2. Review of Speech Recognition
26
2.3.4. Limitations of HMMs
Despite their state-of-the-art performance, HMMs are handicapped by several well-known
weaknesses, namely:
• The First-Order Assumption ... )
i
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i
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. 176 4
j=0
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Speech recognition using neural networks - Chapter 3 potx
... that the neural network may be simulated on a conventional computer, rather than imple-
mented directly in hardware.
3. Review of Neural Networks
50
1982) — or alternatively by neural networks ... recurrent; lay-
ered networks may or may not be recurrent; and modular networks may integrate different
kinds of topologies. In general, unstructured networks use 2-way connections,...
Speech recognition using neural networks - Chapter 4 pps
... by a simple HMM-based recog-
nizer.
Figure 4.3: Time Delay Neural Network.
Integration
Speech
input
Phoneme
output
B
D
G
B
D
G
4.3. NN-HMM Hybrids
63
and neural networks; the speech frames then ... achieving 22 .7% versus 26.0% error for speaker-dependent recognition,
and 30.8% versus 40.8% error for multi-speaker recognition. Training time was reduced to
a reasonable level by us...
Speech recognition using neural networks - Chapter 5 doc
... no English. Janus performs speech trans-
lation by integrating three modules — speech recognition, text translation, and speech gen-
eration — into a single end-to-end system. Each of these modules ... The speech recognition module, for exam-
ple, was originally implemented by our LPNN, described in Chapter 6 (Waibel et al 1991,
Osterholtz et al 1992); but it was later replaced b...
Speech recognition using neural networks - Chapter 6 pps
... Accuracy 37% 44% 55% 60%
Table 6.3: Performance of HMMs using a single gaussian mixture, vs. LPNN.
perplexity
System 7 111 402
HMM-1 55%
HMM-5 96% 70 % 58%
HMM-10 97% 75 % 66%
LVQ 98% 80% 74 %
LPNN 97% ... Predictive Neural Networks
81
6.3. Linked Predictive Neural Networks
We explored the use of predictive networks as acoustic models in an architecture that we
called Linked...
Speech recognition using neural networks - Chapter 8 potx
... 402(b) 111
HMM-1 55%
HMM-5 96% 71 % 58% 76 %
HMM-10 97% 75 % 66% 82%
LPNN 97% 60% 41%
HCNN 75 %
LVQ 98% 84% 74 % 61% 83%
TDNN 98% 78 % 72 % 64%
MS-TDNN 98% 82% 81% 70 % 85%
Table 8.1: Comparative results ... Chapter 7 were developed on this database,
and were never applied to the Conference Registration database.
perplexity test on training set
System 7 111 402(a) 402(b) 111
HMM...
Speech recognition using neural networks - Chapter 9 pptx
... 10 3-1 06
history 27 28
as acoustic models 7, 7 7- 1 50, 151
for speech (review) 5 1 -7 1
See also predictive, classifier, NN-HMM
neurobiology 1, 4, 27
Neurogammon 6
NN-HMM hybrids 7, 71 , 14 7- 1 54
survey 5 7- 7 1
advantages ... 154
winner-take-all networks 42
word
boundaries 84, 87, 141
models 11, 16, 61, 80, 94, 13 8-1 43
recognition 1 4-1 9, 5 5-5 6, 61, 8 4-6 ,...
speech recognition using neural networks
... performance. We will see
that neural networks help to avoid this problem.
1.2. Neural Networks
Connectionism, or the study of artificial neural networks, was initially inspired by neuro-
biology, but it ... advocates.
Figure 2.1: Structure of a standard speech recognition system.
Figure 2.2: Signal analysis converts raw speech to speech frames.
raw
speech
signal
analysis...
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