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.
Other related tools and formant information
- Praat: http://www.fon.hum.uva.nl/praat/
- WaveSurfer: https://sourceforge.net/projects/wavesurfer/
- Perry R. Cook, "Identification of control parameters in an articulatory vocal tract model, with applications to the synthesis of singing", 1990, Ph.D Dissertation, CCRMA https://ccrma.stanford.edu/~kglee/m220c/formant.html
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
- Speech Acoustics Made Easy http://web.archive.org/web/20120914101638/http://www.cochlear.com/files/assets/speech_acoustics_made_easy.pdf
- English vowel word reference http://www.fonetiks.org/engsou2am.html
- Chinese vowel diagram http://en.wikipedia.org/wiki/Chinese_vowel_diagram
- Wiki page http://en.wikipedia.org/wiki/Formant
- The National Center for Voice and Speech http://www.ncvs.org/ncvs/tutorials/voiceprod/tutorial/filter.html
- Linguistics 110 Berkeley http://linguistics.berkeley.edu/~kjohnson/ling110/Homework_assignments/HW7_PlotVowels/PlotYourVowels.pdf
- MATLAB Speech Signal Analysis http://www.phon.ucl.ac.uk/courses/spsci/matlab/lect10.html
- MATLAB Formant Tracker example http://www.mathworks.com/matlabcentral/fileexchange/8959-formant-tracker
- Formant Java example http://chronos.ece.miami.edu/~dasp/SeniorProject/Presentation/416Presentation.pdf
- Digital Bubble Bath - Don H. Johnson Great discussion on formant analysis and practical implementation http://www.clear.rice.edu/elec431/projects96/digitalbb/formants.html
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.