A Review of Deep Learning Techniques for Speech Processing

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Table 12. Comprehensive performance analysis of various models for Keyword Spotting (KS) and Slot Filling
(SF) tasks, evaluated on two benchmark datasets: Google Speech Commands for KS and ATIS for SF.

Keyword Spotting on Google Speech Commands (Accuracy % ↑)

Model

Reference Google Speech Commands V1 12 Google Speech Commands V2 12 Google Speech Commands V2 35

TripletLoss-res15

Wav2KWS

KWT-3
KWT-1
KWT-2

Attention RNN

[560]
[486]
[37]
[37]
[37]
[473]

98.56
97.9

97.49 ±0.15
97.27 ±0.08
97.26±0.18

95.6

98.37
98.5

98.56 ±0.07
98.43±0.08
98.08±0.10

96.9

97.0
97.8

97.69 ±0.09
97.74 ±0.03
96.95±0.14

93.9

Slot Filling on ATIS (F1 ↑)
Model

Reference ATIS

CTRAN

Bi-model with a decoder

Joint BERT

Joint BERT + CRF

SF-ID

Capsule-NLU

[449]
[581]
[70]
[70]
[397]
[641]

0.9846
0.9689
0.961
0.96
0.958
0.952
AReviewofDeepLearningTechniquesforSpeechProcessing