FF                   package:tuneR                   R Documentation

_E_s_t_i_m_a_t_i_o_n _o_f _F_u_n_d_a_m_e_n_t_a_l _F_r_e_q_u_e_n_c_i_e_s _f_r_o_m _a _W_s_p_e_c _o_b_j_e_c_t

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

     Estimation of Fundamental Frequencies from an object of class
     'Wspec'. Additionally, some heuristics are used to distinguish
     silence, noise (and breathing for singers)  from real tones.

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

     FF(object, peakheight = 0.01, silence = 0.2, minpeak = 9, diapason = 440, 
         notes = NULL, interest.frqs = seq(along = object@freq),
         search.par = c(0.8, 10, 1.3, 1.7))
         
     FFpure(object, peakheight = 0.01, diapason = 440, 
         notes = NULL, interest.frqs = seq(along = object@freq),
         search.par = c(0.8, 10, 1.3, 1.7))

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

  object: An object of class 'Wspec'.

peakheight: The peak's proportion of the maximal peak height to be 
          considered for fundamental frequency detection. The default
          (0.01) means peaks smaller than 0.02 times the maximal peak
          height are omitted.

 silence: The maximum proportion of periodograms to be considered as
          silence or noise (such as breathing). The default (0.2) means
          that less than 20 out of 100 periodograms represent silence
          or noise.

 minpeak: If more than 'minpeak' peaks are considered for detection and
          passed argument 'peakheight', such periodograms are detected
          to be silence or noise (if 'silence > 0').

diapason: Frequency of diapason a, default is 440 (Hertz).

   notes: Optional, a vector of integers indicating the notes (in
          halftones from diapason a) that are expected. By applying
          this restriction, the "detection error" might be reduced in
          some cases.

interest.frqs: Optional, either a vector of integers indicating the 
          indices of (fundamental) frequencies in 'object' that are
          expected, or one of the character strings '"bass"',
          '"tenor"', '"alto"' or '"soprano"'. For these voice types,
          only typical frequency ranges are considered for detection.

          By applying this restriction, the "detection error" might be
          reduced in some cases.

search.par: Parameters to look for peaks:

             1.  The first peak larger than 'peakheight *
                'largest_peak'' is taken.

             2.  Its frequency is multiplied by '1+search.par[1]' Now,
                any larger peak between the old peak and that value is
                taken, if (a) it exists and if (b) it is above the
                'search.par[2]'-th Fourier-Frequency.

             3.  Within the interval of frequencies ''current peak' *
                search.par[3:4]', another high peak is looked for. If
                any high peak exists in that interval,  it can be
                assumed we got the wrong partial and the 'real'
                fundamental frequency can be re-estimated  from the
                next two partials. .inen -3 

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

     'FFpure' just estimates the fundamental frequencies for all
     periodograms contained in the  'object' (of class 'Wspec'.

     'FF' additionally uses some heuristics to distinguish silence,
     noise (and breathing for singers)  from real tones. It is
     recommended to use the wrapper function 'FF' rather than 'FFpure'.
     If silence detecion can be omitted by specifying 'silence = 0'.

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

     Vector of estimated fundamental frequencies (in Hertz) for each
     periodogram conatined in 'object'.

_N_o_t_e:

     These functions are still in development and may be changed in due
     course.

_A_u_t_h_o_r(_s):

     Uwe Ligges, ligges@statistik.uni-dortmund.de

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

     'Wspec', 'periodogram' (including an example), and 'noteFromFF'

