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Speech Recognition Experiments on Switchboard Corpus.
The speech recognition experiments show that emotional speech moderately affects the performance of the speech interface.
Speech recognition experiments were also conducted to measure tone recognition as function of the number of electrodes from a 1-electrode map to a 20-electrode map.
We perform speech recognition experiments on Wall Street Journal data, and find that our RF models lead to performances as good as the recurrent neural network LMs but are computationally more efficient in use.
We also performed speech recognition experiments using the recorded explanation utterances.
Audiovisual speech recognition experiments are conducted on the GRID audiovisual corpus.
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The large vocabulary continuous speech recognition experiment results on the Switchboard database indicate that the algorithm proposed in this paper can extract the speech bottleneck features with priori information, and reduce the word error rate in continuous speech recognition.
Their results indicate a slight improvement (in the order of ) in a large vocabulary continuous speech recognition experiment.
We carried out two experiments: (1) a human audiovisual speech recognition experiment and (2) a subjective mean opinion score (MOS) experiment.
A speech recognition experiment showed that the GSS-based dereverberation method achieved an average relative word error reduction rate of 32.6% compared with conventional CMN with beamforming [22].
The order selection methods are adopted in the calculation of the FrFT-MFCC features, and then used in a tonal vowel discrimination test and in a speech recognition experiment.
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