1mlib_SignalLPC2Cepstral_F32m(e3dMiLaILBi)b Library Fumnlcitbi_oSnisgnalLPC2Cepstral_F32(3MLIB)
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6 mlib_SignalLPC2Cepstral_F32 - convert linear prediction coefficients to
7 cepstral coefficients
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10 cc [ flag... ] file... -lmlib [ library... ]
11 #include <mlib.h>
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13 mlib_status mlib_SignalLPC2Cepstral_F32(mlib_f32 *cepst,
14 const mlib_f32 *lpc, mlib_f32 gain, mlib_s32 length,
15 mlib_s32 order);
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19 The mlib_SignalLPC2Cepstral_F32() function converts linear prediction
20 coefficients to cepstral coefficients.
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23 The cepstral coefficients are the coefficients of the Fourier transform
24 representation of the log magnitude spectrum.
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27 The LPC cepstral coefficients can be derived recursively from the LPC
28 coefficients as following.
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30 c(0) = log(G)
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32 m-1 k
33 c(m) = a(m) + SUM --- * c(k) * a(m-k), 1 ≤ m ≤ M
34 k=1 m
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36 m-1 k
37 c(m) = SUM --- * c(k) * a(m-k), m > M
38 k=1 m
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42 See Fundamentals of Speech Recognition by Lawrence Rabiner and Biing-
43 Hwang Juang, Prentice Hall, 1993.
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46 The function takes the following arguments:
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48 cepst The cepstral coefficients.
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51 lpc The linear prediction coefficients.
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54 gain The gain of the LPC model.
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57 length The length of the cepstral coefficients.
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60 order The order of the linear prediction filter.
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64 The function returns MLIB_SUCCESS if successful. Otherwise it returns
65 MLIB_FAILURE.
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68 See attributes(5) for descriptions of the following attributes:
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73 ┌─────────────────────────────┬─────────────────────────────┐
74 │ ATTRIBUTE TYPE │ ATTRIBUTE VALUE │
75 ├─────────────────────────────┼─────────────────────────────┤
76 │Interface Stability │Committed │
77 ├─────────────────────────────┼─────────────────────────────┤
78 │MT-Level │MT-Safe │
79 └─────────────────────────────┴─────────────────────────────┘
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82 mlib_SignalLPC2Cepstral_S16(3MLIB), mlib_SignalLPC2Cep‐
83 stral_S16_Adp(3MLIB), mlib_SignalLPC2Cepstral_F32(3MLIB), attributes(5)
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87SunOS 5.11 2 Mar 2007mlib_SignalLPC2Cepstral_F32(3MLIB)