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- W3216951036 abstract "We simulate the process of feature processing as assumed to be done in thehuman brain. The simulation is based on the principle that the features are processedindependently in critical bands. 30 critical bands are realized by a Gammatone filterbank.The output of each band is segmented into phones. From each segment and each band a‘modulation feature vector’ is extracted assuming that the spectrum of modulation isstationary during the duration of a phone. Using GMMs trained on those modulationfeatures, a recognizer is constructed for each filter. The segments are classified1 intophonemes leading to a phone error rate per band. Given the emission probabilities of theGMMs the probabilities for each phone and for each band are determined. In our approachthese probabilities build the components of a ‘phone feature vector’, which is assumed to beprocessed in the auditory cortex. To the authors knowledge the transformation of themodulation features to phone features is unknown neuro-physically. Yet from perceptiveexperiments we know some statistic properties of the phone features concerning the relationbetween the human phone error rate per band and the human error rate of unfiltered phones[2]. To evaluate this relation we combine the 30 phone feature vectors and construct an ‘allband’recognizer. Classification of segments of Spanish speech using 32 phones leads to an‘all band’ phone error rate of 48% and a phone error rate per band of about 92%. These errorrates deviate significantly from human performance." @default.
- W3216951036 created "2021-12-06" @default.
- W3216951036 creator A5080699027 @default.
- W3216951036 date "2016-01-01" @default.
- W3216951036 modified "2023-09-24" @default.
- W3216951036 title "The Statistics and Phone Error Rates of Bark-Features" @default.
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- W3216951036 hasPublicationYear "2016" @default.
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