Keyword Spotting On Google Speech Commands

评估指标

Google Speech Commands V2 35

评测结果

各个模型在此基准测试上的表现结果

比较表格

模型名称	Google Speech Commands V2 35
hts-at-a-hierarchical-token-semantic-audio	98.0
broadcasted-residual-learning-for-efficient	-
work-in-progress-linear-transformers-for	99.1
importantaug-a-data-augmentation-agent-for	95
learning-efficient-representations-for-3	97.0
hello-edge-keyword-spotting-on	-
effective-combination-of-densenet-andbilstm	-
hello-edge-keyword-spotting-on	-
a-neural-attention-model-for-speech-command	93.9
matchboxnet-1d-time-channel-separable-1	-
efficient-keyword-spotting-using-time-delay	-
end-to-end-keyword-spotting-using-neural	-
multi-layer-attention-mechanism-for-speech	-
hello-edge-keyword-spotting-on	-
hello-edge-keyword-spotting-on	-
ast-audio-spectrogram-transformer	98.11
towards-on-device-keyword-spotting-using-low	98.60
temporal-convolution-for-real-time-keyword	-
ssamba-self-supervised-audio-representation	97.4
keyword-transformer-a-self-attention-model	96.95±0.14
attention-free-keyword-spotting	97.56
end-to-end-audio-strikes-back-boosting	98.15
wav2kws-transfer-learning-from-speech	-
training-keyword-spotters-with-limited-and	-
streaming-keyword-spotting-on-mobile-devices	-
micronets-neural-network-architectures-for	-
subspectral-normalization-for-neural-audio	-
hello-edge-keyword-spotting-on	-
pate-aae-incorporating-adversarial	-
keyword-transformer-a-self-attention-model	97.74 ±0.03
keyword-transformer-a-self-attention-model	97.69 ±0.09
training-keyword-spotters-with-limited-and	-
decentralizing-feature-extraction-with	-
subspectral-normalization-for-neural-audio	-
subspectral-normalization-for-neural-audio	-
neural-architecture-search-for-keyword	-
hello-edge-keyword-spotting-on	-
edgecrnn-an-edgecomputing-oriented-model-of	-
convmixer-feature-interactive-convolution	-
howl-a-deployed-open-source-wake-word	-
masked-modeling-duo-learning-representations	98.5
neural-architecture-search-for-keyword	-