Sentence examples for consonant recognition from inspiring English sources

Dubno, J. & Schaefer, A. Comparison of frequency selectivity and consonant recognition among hearing-impaired and masked normal-hearing listeners.

For consonant recognition, patterns of relative contributions of spectral and temporal information were similar to those in normal hearing subjects.

Figure 6 Consonant-specific results from the consonant recognition experiments: (a) consonant error rates using MFCC.

Overall, FrFT-MFCC seems to outperform the FFT-MFCC-baseline, because consonant recognition is not decreased and tone and vowel discriminability are increased.

This fact might suggest that consonant recognition could degrade, because essentially invalid initial pitch estimates are used for some of the consonants.

However, the proposed methods can achieve better performance even with nonperfect pitch and formant estimation, which is shown by the fact that, although the improvement of the consonant recognition is not so statistically significant, it at least does not decrease despite using essentially invalid initial pitch estimates.

Four more consonants had recognition rates between 70% and 80%.

Four subjects with mild to moderate sensorineural hearing loss were recruited to participate in consonant and vowel recognition tests that used speech stimuli processed through a noise excited vocoder.

An early study confirmed that, at least for partially voiced sounds such as consonant-vowel combinations, speaker recognition is feasible on the basis of nasal co-articulation [ 10].

This task was a recognition task where consonants were presented at a rate of one every three seconds on a Braille board and consisted of eight series each containing three different sequences of stimuli to recall.

Eriksen and Collins [ 6, 7] for example, examined the interval across which two dot patterns could be integrated to allow recognition of a three-consonant trigram.