Unfortunately, when the voice fundamental frequency is high (some high-pitched male voices and all female voices), the wider filter has a tendency to act like the narrower filter, resolving the voice harmonics rather than formants. A filter passband around 50Hz admits just one voice harmonic at a time and each harmonic is recorded individually. A filter passband around 300Hz allows two or three strong voice harmonics at a time to pass through and be registered together as energy peaks. These correspond to the wideband and narrowband settings, respectively, of the spectrograph. The main choice in FFT analysis is between a coarser setting, that shows the formants, and a finer setting, that shows the voice harmonics.LPC has better success with high-pitched voices, but the settings need to be carefully tuned for each speaker. The advantage of FFT is easier setup, the disadavantage is difficulty identifying formants by speakers with higher pitched voices.A strict distinction between resonance as a filter property and the sound energy peaks shaped by it has hardly ever been maintained, and the term formant has usually been applied loosely to both concepts ever since it was coined in the early 20th century to describe vocal tract reonance and the timbre of music intruments.FFT finds the energy distribution in the actual speech sound, whereas LPC estimates the vocal tract filter that shaped that speech. There are two methods for spectral analysis: the fast Fourier transform (FFT) and linear prediction (LPC).Nowadays, a suitable computer program will calculate speech spectra in seconds. From the 1950s onward, this was done by the spectrograph, that burnt a spectrogram onto paper as a permanent record. Formerly, calculation was time-consuming so it was more practical to work on the lab bench using bandpass filters and then measure the filter output at a range of frequencies.Typical uses in phonetics are discovering the spectral properties of the vowels and consonants of a language, comparing the productions of different speakers, or finding characteristics that point forward to speech perception or back to articulation. The purpose of spectral analysis is to find out how acoustic energy is distributed across frequency.
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