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MBE Vocoders. Nima Moghadam Saeed Nari Supervisor Dr. Saameti April 2005 Sharif University of Technology. Outline. Introduction to vocoders MBE vocoder MBE Parameters Parameter estimation Analysis and synthesis algorithm AMBE IMBE. Vocoders - analyzer.

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MBE Vocoders


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mbe vocoders
MBE Vocoders

Nima Moghadam

Saeed Nari

  • Supervisor
  • Dr. Saameti
  • April 2005
  • Sharif University of Technology
outline
Outline
  • Introduction to vocoders
  • MBE vocoder
    • MBE Parameters
    • Parameter estimation
    • Analysis and synthesis algorithm
  • AMBE
  • IMBE
vocoders analyzer
Vocoders - analyzer
  • Speech analyzed first by segmenting speech using a window (e.g. Hamming window)
  • Excitation and system parameters are calculated for each segment
    • Excitation parameters : voiced/unvoiced, pitch period
    • System parameters: spectral envelope / system impulse response
  • Sending this parameters
vocoders synthesizer
Vocoders - Synthesizer

Excitation Signal

White noise/ unvoiced

Pulse train/voiced

System

parameters

Synthesized voice

vocoders
Vocoders
  • But usually vocoders have poor quality
    • Fundamental limitation in speech models
    • Inaccurate parameter estimation
    • Incapability of pulse train/ white noise to produce all voice
      • speech synthesized entirely with a periodic source exhibits a “buzzy” quality, and speech synthesized entirely with a noise source exhibits a “hoarse” quality
  • Potential solution to buzziness of vocoders is to use of mixed excitation models
  • In these vocoders periodic and noise like excitations are mixed with a calculated ratio and this ration will be sent along the parameters
multi band excitation speech model
Multi Band Excitation Speech Model
  • Due to stationary nature of a speech signal, a window w(n) is usually applied to signal
  • The Fourier transform of a windowed segment can be modeled as the product of a spectral envelope and an excitation spectrum
  • In most models is a smoothed version of the original speech spectrum
mbe model cont d
MBE model (Cont’d)
  • the spectral envelope must be represented accurately enough to prevent degradations in the spectral envelope from dominating.
    • quality improvements achieved by the addition of a frequency dependent voiced/unvoiced mixture function.
  • In previous simple models, the excitation spectrum is totally specified by the fundamental frequency w0and a voiced/unvoiced decision for the entire spectrum.
  • In MBE model, the excitation spectrum is specified by the fundamental frequency w0 and a frequency dependent voiced/unvoiced mixture function.
multi banding
Multi Banding
  • In general, a continuously varying frequency dependent voiced/unvoiced mixture function would require a large number of parameters to represent it accurately. The addition of a large number of parameters would severely decrease the utility of this model in such applications as bit-rate reduction.
  • To further reduce the number of these binary parameters, the spectrum is divided into multiple frequency bands and a binary voiced/unvoiced parameter is allocated to each band.
  • MBE model differs from previous models in that the spectrum is divided into a large number of frequency bands (typically 20 or more), whereas previous models used three frequency bands at most .
multi banding1
Multi Banding

V/UV

information

Original

spectrum

Noise

spectrum

Spectral

envelope

Excitation

spectrum

Periodic

spectrum

Synthetic

spectrum

mbe parameters
MBE Parameters
  • The parameters used in MBE model are:
    • spectral envelope
    • the fundamental frequency
    • the V/UV information for each harmonic
    • and the phase of each harmonic declared voiced. The phases of harmonics in frequency bands declared unvoiced are not included since they are not required by the synthesis algorithm
parameter estimation
Parameter Estimation
  • In many approaches (LPC based algorithms) the algorithms for estimation of excitation parameters and estimation of spectral envelope parameters operate independently.
  • These parameters are usually estimated based on heuristic criterion without explicit consideration of how close the synthesized speech will be to the original speech.
    • This can result in a synthetic spectrum quite different from the original spectrum.
  • In MBE the excitation and spectral envelope parameters are estimated simultaneously so that the synthesized spectrum is closest in the least squares sense to the spectrum of the original speech “analysis by synthesis”
parameter estimation cont d
Parameter Estimation (Cont’d)
  • the estimation process has been divided into two major steps.
    • In the first step, the pitch period and spectral envelope parameters are estimated to minimize the error between the original spectrum and the synthetic spectrum.
    • Then, the V/UV decisions are made based on the closeness of fit between the original and the synthetic spectrum at each harmonic of the estimated fundamental.
parameter estimation cont d1
Parameter Estimation (cont’d)
  • The parameters estimated by minimizing the following error criterion:
    • Where
  • The error in an interval

is minimized at:

pitch estimation and spectral envelope
Pitch Estimation and Spectral Envelope
  • An efficient method for obtaining a good approximation for the periodic transform P ( w ) in this interval is to precompute samples of the Fourier transform of the window w (n) and center it around the harmonic frequency associated with this interval.
  • For unvoiced frequency intervals, the envelope parameters are estimated by substituting idealized white noise (unity across the band) for |E (a)| in previous formulas which reduces to averaging the original spectrum in each frequency interval.
  • For unvoiced regions, only the magnitude of A, is estimated since the phase of A, is not required for speech synthesis.
more about pitch estimation
More about pitch estimation
  • Experimentally, the error Etends to vary slowly with the pitch period P
  • the initial estimate is obtained by evaluating the error for integer pitch periods
  • Since integer multiples of the correct pitch period have spectra with harmonics at the correct frequencies, the error E will be comparable for the correct pitch period and its integer multiples.
more about pitch estimation cont d
More about pitch estimation (Cont’d)

Error/Pitch

Speech

segment

Original

spectrum

Original and

Synthetic

P=42.48

Original and

Synthetic

P=42

v uv decision
V/UV Decision
  • The voiced/unvoiced decision for each harmonic is made by comparing the normalized error over each harmonic of the estimated fundamental to a threshold
  • When the normalized error over mth harmonic is below the threshold, this frame will be marked as voiced else unvoiced
analysis algorithm flowchart
Analysis Algorithm Flowchart

start

Select initial pitch period

(Dynamic programming

Pitch tracker)

Select V/UV spectral

Envelope parameters

For each freq. band

Window

Speech

segment

Refine initial pitch period

(frequency domain approach)

Stop

Compute error vs. pitch period

Autocorrelation approach

Make V/UV decision for each

Frequency band

speech synthesis
Speech Synthesis
  • The voiced signal can be synthesized as the sum of sinusoidal oscillators with frequencies at the harmonics of the fundamental and amplitudes set by the spectral envelope parameters (The time domain method).
  • The unvoiced signal can be synthesized as the sum of bandpass filtered white noise
  • The frequency domain method was selected for synthesizing the unvoiced portion of the synthetic speech.
synthesis algorithm block diagram
Synthesis algorithm block diagram

V/UV

Decision

Voiced envelope

samples

Voiced envelope

samples

Separate

Voiced/Unvoiced

Envelope samples

Bank of

Harmonic

oscillators

Voiced

speech

Envelope

samples

Unvoiced envelope

samples

Unvoiced envelope

samples

Unvoiced envelope

samples

Linear

interpolation

White noise

sequence

STFT

Replace

envelope

Weighted

Overlap-add

Unvoiced

speech

mbe synthesis algorithm
MBE Synthesis algorithm
  • First, the spectral envelope samples are separated into voiced or unvoiced spectral envelope samples depending on whether they are in frequency bands declared voiced or unvoiced
  • Voiced envelope samples include both magnitude and phase, whereas unvoiced envelope samples include only the magnitude.
  • Voiced speech is synthesized from the voiced envelope samples by summing the outputs of a band of sinusoidal oscillators running at the harmonics of the fundamental frequency
mbe synthesis algorithm voiced
MBE Synthesis algorithm (Voiced)
  • The phase function is determined by an initial phase and a frequency track as follows:
  • The frequency track is linearly interpolated between the mth harmonic of the current frame and that of the next frame by:
mbe synthesis algorithm unvoiced
MBE Synthesis algorithm (Unvoiced)
  • Unvoiced speech is synthesized from the unvoiced envelope samples by first synthesizing a white noise sequence.
  • For each frame, the white noise sequence is windowed and an FFT is applied to produce samples of the Fourier transform
  • In each unvoiced frequency band, the noise transform samples are normalized to have unity magnitude. The unvoiced spectral envelope is constructed by linearly interpolating between the envelope samples |Am(t)|.
  • The normalized noise transform is multiplied by the spectral envelope to produce the synthetic transform. The synthetic transforms are then used to synthesize unvoiced speech using the weighted overlap-add method.
mbe synthesis cont d
MBE Synthesis (Cont’d)
  • The final synthesized speech is generated by summing the voiced and unvoiced synthesized speech signals

Voiced

speech

Synthesized

speech

+

Unvoiced

speech

advanced mbe ambe
Advanced MBE (AMBE)
  • MBE coding rate at 2400 bps
  • AMBE coding rate at 1200/2400 bps
  • Four new features
    • Enhanced V/UV decision
    • Initial pitch detection
    • Refined pitch determination
    • Dual rate coding
enhanced v uv decision
Enhanced V/UV decision
  • divide the whole speech frequency band into 4 subbands and 2 subbands for 2.4 kbps and 1.2 kbps respectively.
  • That is to say only 4 bits and 2 bits are used to encode U/V decisions for 2.4 kb/s and 1.2 kb/s vocoder respectively.
initial pitch detection
Initial pitch detection
  • MBE takes 2 steps to detect the refined initial pitch period
    • Spectrum matching technique to find the initial pitch period
    • Using DTW-based (Discrete Time Wrapping) technique to smooth the estimation
  • Computational complexity is very high
  • In MBE, a modified three-level center clipped auto-correlation method is used to detect the initial pitch period, and also use a simple smoothing method to correct the pitch errors.
redefined pitch determination
Redefined pitch determination
  • To find the best pitch the basic method is to compute the error between the original speech spectrum and the shaped voiced speech spectrum by first supposing a pitch period
  • The supposed pitch of which the spectrum error is minimum is chosen as the last pitch
  • To reduce the computational complexity, AMBE uses a 256- point FFT to get the speech spectrum, and 5-point window spectrum is used to form the voiced harmonic spectrum.
  • To get the refined pitch, AMBE perform seven times of spectrum matching process. In every time. AMBE first set a supposed pitch, then shape a harmonic spectrum over the overall frequency band according to the supposed pitch and window spectrum, and an error can be calculated by subtracting the shaped spectrum from speech spectrum. After the seven times of matching process, the refined pitch can easily be determined
improved mbe imbe
Improved MBE (IMBE)
  • A 2400 bps coder based on MBE
  • Substantially better than U.S government standard LPC-10e
  • The parameters of the MBE speech model :
    • the fundamental frequency
    • voiced/unvoiced information
    • the spectral envelope.
imbe algorithm
IMBE algorithm
  • estimate the excitation and system parameters which minimize the distance between the original and synthetic speech spectra (analysis by synthesis)
  • Once these parameters are estimated, voiced/unvoiced decisions are made by comparing the spectral error over a series of harmonics to a prescribed threshold
imbe block diagram
IMBE block diagram
  • IMBE algorithm block diagram
imbe coding
IMBE Coding
  • IMBE offered in 2.4, 4.8 and 8.0 kbps
  • Analysis and synthesis routines are the same except the bit allocation
  • The fundamental frequency needs accuracy of about l Hz. and requires about 9 bits per frame.
  • The V/UV decisions are encoded with one bit per decision.
  • The remaining bits are allocated to error control and the spectral envelope information.