Basic SpectrogramLab 8

Spectrograms

Spectrograph: Produces visible patterns of acoustic energy called spectrograms

Spectrographic Analysis: Acoustic signal changes rapidly & continuously Need a dynamic analysis revealing spectral

features Short term running spectrum

Spectrographic Analysis

Time, Frequency & intensity Time (horizontal axis): Phonetic elements

will be from left to right

Frequency (Vertical axis): Increasing in

upward direction

Intensity represented by a gray scale or as

variations in darkness

Dimensions of SpectrogramsA. Burst of noise B. Vowel with 4 formants

C. Noise with high frequency energyTime

Source/FilterResonator & Source Energy

Filter = Vocal tract• Energy passed in a frequency selective manner

• Production of different vowels changes the filter shape Source = Harmonic spectrum of voicing

• Fundamental frequency & its harmonics

• Source spectrum is the acoustic energy activating the formants

Source-filter theory of vowel production: The energy form the source (vibrating vocal folds) is

modified by the resonance characteristics of the filter (vocal tract)

Formants- Filter

Are formed through resonation of sound in the vocal tract (filter function)

Can only see through a wide band spectrogram

F1F2F2

Harmonics- Source

Harmonics (Spectrum)

Harmonics(Spectrogram)

Source-Filter Theory

Source-Filter

Wide Band vs. Narrow Band

Wide Band: analyzing filter wide, 300-400 Hz Good to show formants because they have a

wide spread of acoustic energy

Narrow Band: analyzing filter is of higher resolution, 100 Hz Good to show the harmonics of source

spectrum

Bandwidth

NarrowBandwidth

(Harmonics)

WideBandwidth(Formants)

Continuous Spectrum Bandwidth

Vowel: Wide Band vs. Narrow Band

Fricative noise: Above 3 or 4 kHz

Diphthong: Horizontal bands of energy

Wide Band Spectrogram

Digital Signal Processing

Basic objective of digital signal processing: Convert the analog acoustic signal (Panel A) to a digital

form (series of #’s) How do we get a waveform into a digital computer?

• Analog-Digital conversion (A-D): results in samples of time and amplitude

Correct sampling rate is important to reconstruct the wave form

• Sampling rate must be 2x the bandwidth of analysis: Nyquist Frequency

– Ex. Sample speech with a bandwidth of 5000 Hz, than the sampling rate should be 10,000 Hz

Analog-Digital Conversion

b. Time sampling intervals

Laboratory

Part I: Recording the sample- Sampling rate Set sampling rate for shortest duration possible Sustain /a/: **open 3 views to print all samples on 1 screen

• Sample at 20,000 samples/sec; look at 5-6 cycles

• Sample at 5,000 samples/sec; look at 5-6 cycles

• Sample at 2,500 samples/sec; look at 5-6 cycles What happens as sampling rate drops Narrow band filter each sample (print each)

Laboratory

Part II: Filter bandwidth Record “I am tall”

• Wide band and narrow band the statement– Find the following characteristics on one or both of the

spectrograms:

» Harmonic lines

» Formant bands

» Vertical striations

» Acoustic indication of release of air pressure for /t/

– Which has better frequency resolution? Time resolution? Which can you determine formant bands?

Laboratory

Part II: Cont. Make wide and narrow band spectrograms of the

following, stressing the underlined word:• “I am tall”

• “I am tall”

• “I am tall”

• “I am tall?” Which spectrograms show the intonation contour?

Mark the contour on one of your printouts

Laboratory

Part III: Changing the Filter Say /i:u:i/ without changing intonation

• Prepare 2 spectrograms of this utterance– 1st- 2x’s your fundamental frequency

– 2nd- no more than half your fundamental

• Answer questions:– Label each vowel on each spectrogram

– Harmonics

– Formants