Presentation is loading. Please wait.

Presentation is loading. Please wait.

Frequency Domain Coding of Speech 主講人:虞台文. Content Introduction The Short-Time Fourier Transform The Short-Time Discrete Fourier Transform Wide-Band Analysis/Synthesis.

Similar presentations


Presentation on theme: "Frequency Domain Coding of Speech 主講人:虞台文. Content Introduction The Short-Time Fourier Transform The Short-Time Discrete Fourier Transform Wide-Band Analysis/Synthesis."— Presentation transcript:

1 Frequency Domain Coding of Speech 主講人:虞台文

2 Content Introduction The Short-Time Fourier Transform The Short-Time Discrete Fourier Transform Wide-Band Analysis/Synthesis Sub-Band Coding

3 Frequency Domain Coding of Speech Introduction

4 Speech Coders Waveform Coders – Attempt to reproducing the original waveform according to some fidelity criteria – Performance: successful at producing good quality, robust speech. Vocoders – Correlated with speech production model. – Performance: more fragile and more model dependent. – Lower bit rate

5 Frequency-Domain Coders Sub-band coder (SCB). Adaptive Transform Coding (ATC). Multi-band Excited Vocoder (MBEV). Noise Shaping in Speech Coders.

6 Classification of Speech Coders

7 Frequency Domain Coding of Speech The Short-Time Fourier Transform

8 Definition of STFT Interpretations: Filter Bank Interpretation Block Transform Interpretation

9 Filter Bank Interpretation  is fixed at  0. f ( m ) Analysis Filter

10 Filter Bank Interpretation...... h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) x(n)x(n)

11 Modulation   00

12 Filter Bank Interpretation   00 Lowpass Filter Modulation

13 Filter Bank Interpretation...... h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) x(n)x(n) Modulated Subband signals

14 Block Transform Interpretation n is fixed at n 0. Windowed Data Analysis Window FT of Windowed Data

15 Block Transform Interpretation n is fixed at n 0. n1n1 n2n2 n3n3...... nrnr

16 Analysis/Synthesis Equations Analysis Synthesis In what condition we will have

17 Analysis/Synthesis Equations Analysis Synthesis Replace r with n+r

18 Analysis/Synthesis Equations Analysis Synthesis Therefore, if

19 Analysis/Synthesis Equations More general, Analysis Synthesis Therefore, if

20 Examples

21 h (0) x ( n )

22 Examples

23 Frequency Domain Coding of Speech The Short-Time Discrete Fourier Transform

24 Definition of STDFT Analysis: Synthesis: In what condition we will have

25 Synthesis 1

26 We need only one period. Therefore, the condition is respecified as:

27 Implementation Consideration n Frequency k 0 Spectrogram

28 Sampling n Frequency k 0 Spectrogram R2R2R3R3R4R4R

29 Sampled STDFT Analysis: Synthesis: In what condition we will have

30 Sampled STDFT Analysis: Synthesis: In what condition we will have

31 Frequency Domain Coding of Speech Wide-Band Analysis/Synthesis

32 Short-Time Synthesis --- Filter Bank Summation STFT h(n)h(n) h(n)h(n) x(n)x(n) Lowpass Filter

33 Short-Time Synthesis --- Filter Bank Summation STFT

34 Short-Time Synthesis --- Filter Bank Summation  |H(e j  )|  |H k (e j  )| kk Lowpass filterBandpass filter

35 Short-Time Synthesis --- Filter Bank Summation hk(n)hk(n) hk(n)hk(n) x(n)x(n) Bandpass Filter h(n)h(n) h(n)h(n) x(n)x(n) Lowpass Filter Lowpass representation of for the signal in a band centered at  k.

36 Short-Time Synthesis --- Filter Bank Summation hk(n)hk(n) hk(n)hk(n) x(n)x(n) Bandpass Filter h(n)h(n) h(n)h(n) x(n)x(n) Lowpass Filter Encoding one bandDecoding one band

37 Short-Time Synthesis --- Filter Bank Summation h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... Analysis Synthesis

38 Short-Time Synthesis --- Filter Bank Summation h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... Analysis Synthesis

39 Short-Time Synthesis --- Filter Bank Summation h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... Analysis Synthesis

40 Equal Spaced Ideal Filters 11 22 33 44 55 22  1 0 N = 6

41 Equal Spaced Ideal Filters h1(n)h1(n) x(n)x(n) h0(n)h0(n) hN1(n)hN1(n)...... What condition should be satisfied so that y(n)=x(n)?

42 Equal Spaced Ideal Filters Equal spaced sampling of H ( e j  ) Inverse discrete FT of H ( e j  ) Time-Aliased version of h ( n )

43 Equal Spaced Ideal Filters Consider FIR, i.e., h(n) is of duration of L samples. 0 L1L1 n h(n)h(n) In case that N  L,

44 Equal Spaced Ideal Filters

45 h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... 0 L1L1 n h(n)h(n) x(n) can always be Reconstructed if N  L,

46 Equal Spaced Ideal Filters h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... 0 L1L1 n h(n)h(n) x(n) can always be Reconstructed if N  L, Does x(n) can still be reconstructed if N<L? If affirmative, what condition should be satisfied?

47 Equal Spaced Ideal Filters h1(n)h1(n) h1(n)h1(n) x(n)x(n) h0(n)h0(n) h0(n)h0(n) hN1(n)hN1(n) hN1(n)hN1(n)...... p(n)p(n)

48 p(n)p(n) Signal can be reconstructed If it equals to  ( n  m ).

49 Typical Sequences of h (n) Ideal lowpass filter with cutoff at  /N. 0 NN 2N2N N2N2N3N3N4N4N p(n)p(n) N 0 NN 2N2N N2N2N3N3N4N4N h(n)h(n) 1/N

50 Typical Sequences of h (n) 0 NN 2N2N N2N2N3N3N4N4N p(n)p(n) N 0 NN 2N2N N2N2N3N3N4N4N h(n)h(n) h(0) LL 2L2L L2L2L3L3L4L4L N  LN  L

51 Typical Sequences of h (n) 0 NN 2N2N N2N2N3N3N4N4N p(n)p(n) N 0 NN 2N2N N2N2N3N3N4N4N h(n)h(n) h(0) 1/N A causal FIR lowpass filter

52 Typical Sequences of h (n) 0 NN 2N2N N2N2N3N3N4N4N p(n)p(n) N 0 NN 2N2N N2N2N3N3N4N4N h(n)h(n) h(0) 1/N A causal IIR lowpass filter

53 Filter Back Implementation for a Single Channel hk(n)hk(n) x(n)x(n) h(n)h(n) x(n)x(n) Analysis Synthesis

54 hk(n)hk(n) x(n)x(n) h(n)h(n) x(n)x(n) Filter Back Implementation for a Single Channel R:1 1:R Analysis Synthesis Decimator Interpolator

55 hk(n)hk(n) x(n)x(n) h(n)h(n) x(n)x(n) Filter Back Implementation for a Single Channel R:1 1:R Analysis Synthesis Decimator Interpolator Depends on the bandwidth of h(n). R=?

56 Frequency Domain Coding of Speech Sub-Band Coding

57 Analysis Synthesis Filter Bank Implementation (Direct Implementation)...... h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) x(n)x(n)...... R:1 1:R............ f(n)f(n) f(n)f(n) f(n)f(n) f(n)f(n) f(n)f(n) f(n)f(n) f(n)f(n) f(n)f(n) x(n)x(n) Complex Channels R=2  B Bandwidth B/2

58 Filter Bank Implementation (Practical Implementation) 0 B kk 0 B  k 0 B/2  B/2 0 B/2  B/2 0 BB 0 B 0 BB B

59 Filter Bank Implementation (Practical Implementation)............ h(n)h(n) h(n)h(n) h(n)h(n) h(n)h(n) x(n)x(n)......

60 ...... h(n)h(n) h(n)h(n) x(n)x(n)...... h(n)h(n) h(n)h(n)

61 ...... h(n)h(n) h(n)h(n) x(n)x(n)...... h(n)h(n) h(n)h(n) D:1 Why?

62 Filter Bank Implementation (Practical Implementation)...... h(n)h(n) h(n)h(n) x(n)x(n)...... h(n)h(n) h(n)h(n) D:1

63 ...... h(n)h(n) h(n)h(n) x(n)x(n)...... h(n)h(n) h(n)h(n) Filter Bank Implementation (Practical Implementation)

64 x(n)x(n)...... h(n)h(n) h(n)h(n)...... h(n)h(n) h(n)h(n) D:1 2D:1

65 Filter Bank Implementation (Practical Implementation) ADPCM CODEC...... h(n)h(n) h(n)h(n)...... h(n)h(n) h(n)h(n) 2D:1 f(n)f(n) f(n)f(n)...... f(n)f(n) f(n)f(n)...... Filter Bank Analysis Filter Bank Analysis Sub-Band Coder Modification Sub-Band Coder Modification Filter Bank Synthesis Filter Bank Synthesis


Download ppt "Frequency Domain Coding of Speech 主講人:虞台文. Content Introduction The Short-Time Fourier Transform The Short-Time Discrete Fourier Transform Wide-Band Analysis/Synthesis."

Similar presentations


Ads by Google