norm                   package:emu                   R Documentation

_N_o_r_m_a_l_i_s_e _s_p_e_e_c_h _d_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Normalises speech data

_U_s_a_g_e:

     norm(data, speakerlabs, type="gerst", rescale=FALSE)

_A_r_g_u_m_e_n_t_s:

    data: A matrix of data. Can be either an n-columned matrix or a
          trackdata object as returned by 'track'. 

speakerlabs: A parallel vector of speaker labels. 

    type: The type of extrinsic normalisation to be performed on data.
          type can be '"nearey"', '"cen"', '"lob"', '"gerst"'
          (default), for normalisation according to Nearey, centroid
          method, Lobanov, or Gerstman. 

 rescale: Currently only works for Lobanov normalisation. The
          normalised values are multiplied by the standard deviation
          and then the mean is added, where the standard deviation and
          mean are across all original speakers' unnormalised data. 

_D_e_t_a_i_l_s:

     Types of normalisation: '"nearey"', Nearey : Find the log of each
     data element and subtract from each the mean of the logarithmic
     data.  '"cen"', centroid: Find the mean of the data column and
     subtract it from each data element in that column.  '"lob"',
     Lobanov: Find the mean and standard deviation of the data.
     Subtract the mean from each data element and devide each result by
     the standard deviation.  "gerst", Gerstman: Subtract from the data
     the minimun formant value then devide by the formant range.

_V_a_l_u_e:

     Normalised values of data are retuned, having the same structure
     as data.

_S_e_e _A_l_s_o:

     track

