Implementation of pitch detection algorithms for pathological voices
Citations
42 citations
Cites background from "Implementation of pitch detection a..."
...Voice comparison [1] is a difficult problem to solve because the voice of a person may change due to the emotion, age-gap, and throat infection [2]....
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9 citations
Cites background from "Implementation of pitch detection a..."
...Voice disorder has been affecting various social categories accounting for around 25% of the world population [1], such as voice-related professionals like teachers [2], elderly people, smokers, patients in respiratory, nasal and larynx diseases [3] and so on....
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2 citations
Cites methods from "Implementation of pitch detection a..."
...Cepstral coefficients are calculated as shown in(6)[9]: c τ = F log( F x[n] 2 (6) where F denotes the inverse Fourier transform and x[n] is the discrete signal and F{x[n]} 2 is the power spectrum estimatedof the signal....
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References
3,103 citations
1,565 citations
"Implementation of pitch detection a..." refers background in this paper
...This is due to the fact that the shape and dimension of the above mentioned parameters varies from person to person [2]....
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984 citations
"Implementation of pitch detection a..." refers background in this paper
...The modified F˳ is corresponds to vocal chords and those concerning modification of vocal chords [1]....
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793 citations
"Implementation of pitch detection a..." refers methods in this paper
...We apply error correction method to remove discontinuity of pitch markers [10]....
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...Thus, we calculate pitch for every sample [10]....
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572 citations
"Implementation of pitch detection a..." refers methods in this paper
...It is time domain method based on the center-clipping method [9]....
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