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Latest commit 390d152 Dec 30, 2016 @fulldecent update pods

README.md

FORMANT PLOTTER

This is an iOS project to analyze formants. The user speaks and the formant is plotted on the screen immediately. It is designed for speaking a single vowel syllable. It will try to isolate the vowel sound from any surrounding consonants if it can.

Formant Research

Other related tools and formant information

Vowel formant chart:

vowel       F1  F2  F3
ee  male    270 2290    3010
    female  310 2790    3310
    child   370 3200    3730
e   male    530 1840    2480
    female  610 2330    2990
    child   690 2610    3570
ae  male    660 1720    2410
    female  850 2050    2850
    child   1030    2320    3320
ah  male    730 1090    2440
    female  590 1220    2810
    child   680 1370    3170
oo  male    300 870 2240
    female  370 950 2670
    child   430 1170    3260

The Formant Plotter

The program starts in green state. When the user starts talking (i.e. RMS goes above 0dBm for at least 0.1 seconds), the program goes into listening state and records the sound. When the user stops talking (i.e. RMS goes below 0dBm for at least 0.1 seconds), the program returns to ready state and draws graphs.

Graph drawing is done as follows: The recorded sound is truncated to remove the first and last 10% of the data. Then perform a Fast Fourier Transform (FFT) with autocorrelation. The result is plotted linear from 0 - 4000 Hz on the X axis and from -60 to 0 dB log scale on the Y axis.

The second graph is drawn as follows: An image is placed on the background for the chart (you create an image to start with) and two dots are plotted on the chart, representing the highest and lowest sample value from the recording. That's it.

The correct algorithm which takes the FFT results which were plotted above and creates the vowel plot is discussed in Formant Research above.

Some potential next steps include:

  • Use autocorrelation to increase trimming accuracy
  • Windowing on the truncated sound buffer so that edge samples have an attenuated effect
  • Root polishing. The code has been written but commented out (please see PlotView.m). If we can test and refine this part, we will have better estimates of roots of LPC polynomials, and formant frequencies. We may not want VERY accurate estimates of formant frequencies and may not need root polishing.
  • Elimination of weak roots (far away from unit circle). They do not produce a peak in H(w) and should be ignored. I hope that if we reduce order of LPC, we may not see such weak roots. This should be investigated after reduction of LPC filter order.