Characteristics of speech signal

Speech signals have special statistical and spectral properties. Speech coders use these to cut the bit rate below 64 kbps PCM.

1. Limited bandwidth – Speech covers about 50 Hz–10 kHz, but almost all intelligibility lies in 300–3400 Hz, so telephone speech is sampled at 8 kHz.
2. Non-uniform amplitude distribution – The pdf of speech amplitude is peaked at zero (Laplacian/gamma-like): small amplitudes are much more frequent than large ones. This leads to non-uniform (μ-law, A-law) and adaptive quantization.
3. High sample-to-sample correlation – At 8 kHz sampling, adjacent samples are strongly correlated (coefficient often above 0.85). The future sample can be predicted from past ones, which is used by DPCM, ADPCM and LPC.
4. Non-flat (non-white) spectrum – Energy falls with frequency, and there are resonance peaks called formants due to the vocal tract. Sub-band and transform coders exploit this by allocating bits to strong bands.
5. Voiced and unvoiced sounds – Voiced sounds (vowels) are quasi-periodic, produced by vibrating vocal cords; the repetition rate is the pitch (about 80–160 Hz for men, 160–350 Hz for women). Unvoiced sounds (s, f, sh) are random, noise-like. Vocoders use a pulse or noise excitation accordingly.
6. Short-term stationarity – The vocal tract changes slowly, so speech is nearly stationary over 10–30 ms. Coders process speech in frames of about 20 ms.
7. Long-term periodicity – Successive pitch periods look similar; long-term (pitch) predictors remove this redundancy.
8. Silence/pauses – In a conversation each speaker is active only about 40% of the time. Voice activity detection and discontinuous transmission use this to save power and reduce interference.
9. Perceptual properties – The ear is fairly insensitive to phase and to noise masked by nearby strong components; perceptual weighting in CELP uses this.