Programmer Guide/Command Reference/EVAL/f0ac: Difference between revisions
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F0 detection using autocorrelation, as described by Paul Boersma (1993: Accurate Short-Term Analysis of the Fundamental Frequency and the Harmonics-To-Noise Ratio of a Sampled Sound. Proceedings of the IFA. Vol 17. pp 97-110). | F0 detection using autocorrelation, as described by Paul Boersma (1993: Accurate Short-Term Analysis of the Fundamental Frequency and the Harmonics-To-Noise Ratio of a Sampled Sound. Proceedings of the IFA. Vol 17. pp 97-110). | ||
Revision as of 15:10, 20 April 2011
F0 detection using autocorrelation, as described by Paul Boersma (1993: Accurate Short-Term Analysis of the Fundamental Frequency and the Harmonics-To-Noise Ratio of a Sampled Sound. Proceedings of the IFA. Vol 17. pp 97-110).
Usage:
f0ac(x, sr, hopsize, minf0, maxf0, nppw, nMaxCandidates, thSilence, thVoice, costOct, costOctJump, costVUV)
Parameters:
- x
- The signal vector.
- sr
- The sampling rate in Hertz.
- hopsize
- The hop size in seconds. The default is
0.
- minf0
- The minimum f0 in Hertz. The default is
75.
- maxf0
- The maximum f0 in Hertz. The default is
400.
- nppw
- The number of periods per window. The default is
3.
- nMaxCandidates
- The maximum number of candidates. The default is
15.
- thSilence
- The silence threshold. The default is
0.05.
- thVoice
- The voicing threshold. The default is
0.4.
- costOct
- The octave cost. The default is
0.01.
- costOctJump
- The octave jump cost. The default is
0.4.
- costVUV
- The voiced/unvoiced transition cost. The default is
0.2.
Result:
An f0 vector in Hertz.
