Method and apparatus for speech coding and decoding

Claim 2

The method of claim 1, wherein said short-term filter is a filter having a number NS < 20 filter taps, and said step of deriving filter parameters for said short-term filter comprises deriving coefficient values for each of said NS taps.

Claim 3

The method of claim 1, wherein F is less than or equal to 5,

Claim 4

The method of claim 1, wherein D is less than or equal to 10.

Claim 5

The method of claim 4, wherein R is less than 16.

Claim 6

The method of claim 2, wherein said gain factor is adjusted by backward adaptation.

Claim 7

The method of claim 1, wherein said step of comparing comprises forming for each candidate signal a difference signal representing the difference between said input frame and said candidate signal, frequency weighting said difference signals to form weighted difference signals that emphasize frequencies of greater perceptual significance, and determining the minimum value for said weighted difference signals.

Claim 8

The method of claim 7, wherein said frequency weighting is accomplished by filtering said difference signals in a filter, the coefficients of which are determined by an analysis of the input frame signals.

Claim 9

The method of claim 8, wherein said analysis of the input frame signals comprises an LPC analysis of the unquantized input frame signals.

Claim 10

The method of claim 2, wherein NS = 10.

Claim 11

The method of claim 1 wherein said step of deriving filter parameters for said long-term filter comprises deriving a pitch period parameter and NL > 1 filter tap coefficient parameters.

Claim 12

The method of claim 11, wherein NL = 3.

Claim 13

The method of claim 1 further comprising the steps of determining whether or not said frame of sampled input signals is part of a sequence of voiced information, and making available said filter parameters for said long-term filter for decoding when said frame of sampled input signals is part of a sequence of voiced information.

Claim 14

The method of claim 13, wherein said step of determining comprises making a preliminary voiced/non-voiced decision for each frame, and determining that the present frame is not part of a sequence of voiced speech frames if the preliminary decision for the present frame and for each of a predetermined number, K, of immediately preceding frames is non-voiced.

Claim 15

The method of claim 14, wherein said step of making a preliminary voiced/non-voiced decision comprises establishing a threshold value for samples in the input frame, adjusting said threshold for each succeeding sample in the input frame by multiplying the existing threshold by a predetermined factor T < 1 whenever whenever the value for the present sample is less than or equal to the existing threshold, and setting the threshold to the value of the present sample when it exceeds the existing threshold, forming for each input frame a reference value based on the threshold values for the samples in the frame, and making a decision that the current frame is voiced whenever the values for samples in the current frame satisfy a first predetermined condition relative to said reference value, and making a preliminary decision that the current frame is non-voiced whenever the values for samples in the current frame satisfy a second predetermined condition relative to said reference value.

Claim 16

The method of claim 15, wherein said step of forming a reference value comprises forming an average of the threshold function for the samples of the current frame, said first predetermined condition comprises having the peak magnitude for samples in the current frame exceeding half of said reference value, said second predetermined condition comprises having the peak magnitude for samples in the current frame failing to exceed 2% of said reference value, and said method further comprises determining the optimal tap value for a one-tap predictor based on the current input frame, and whenever said first and second predetermined conditions are not satisfied, determining that said present frame is voiced if said one-tape predictor tap value is greater than a predetermined value.

Claim 17

The method of claim 15, wherein said step of forming a reference value comprises forming an average of the threshold function for the samples of the current frame, said first predetermined condition comprises having the peak magnitude for samples in the current frame exceeding half of said reference value, said second predetermined condition comprises having the peak magnitude for samples in the current frame failing to exceed 2% of said reference value, and said method further comprises determining the normalized first-order autocorrelation coefficient of the samples of the present frame, and whenever said first and second conditions are not satisfied, determining that said current frame is voiced whenever said autocorrelation coefficient is greater than a predetermined value.

Claim 18

method of claim 15, wherein said step of forming a reference value comprises forming an average of the threshold function for the samples of the current frame, said first predetermined condition comprises having the peak magnitude for samples in the current frame exceeding half of said reference value, said second predetermined condition comprises having the peak magnitude for samples in the current frame failing to exceed 2% of said reference value, and said method further comprises determining the zero-crossing rate for the samples of the present frame, and whenever said first and second conditions are not satisfied, determining that said current frame is voiced whenever said zero-crossing rate is greater than a predetermined value.

Claim 19

The method of claim 14, wherein K = 3.

Claim 20

The method of claim 11, wherein said step of deriving said pitch period for said long term filter comprises performing an L-order LPC analysis of the signals in the input frame, performing an inverse LPC filtering of said input frame signals based on filter coefficients derived from said L-order analysis to determine a prediction residual signal, and extracting said pitch period by correlation peak picking of a function of said prediction residual signal.

Claim 21

The method of claim 20, wherein said function of said prediction residual signal is a low-pass filtered, time-decimated function of said prediction residual signal.

Claim 22

The method of claim 20, wherein said correlation peak picking is performed for time lags extending over a range of possible pitch period durations, and said extraction comprises selecting the time lag yielding the largest correlation.

Claim 23

The method of claim 21, wherein said correlation peak picking is performed for time lags extending over a range of possible pitch period durations, and said extraction comprises selecting the time lag yielding the largest correlation, and adjusting said selected time lag to account for said time-decimation to yield a pitch period value p0.

Claim 24

The method of claim 23 further comprising eliminating a false multiple of the true pitch period from said adjusted time lag by establishing the pitch period determined for the previous period as a reference value, and selecting a pitch period value p1 for the present frame which is indicated by a peak in said peak picking which peak is within a preselected range of said reference value, the reference value for the first frame in a sequence of frames having a significant pitch component being selected as the peak of said correlation function without reference to a preceding pitch period value.

Claim 25

The method of claim 24 further comprising resolving possible conflicts between a value for a pitch period p1 within said preselected range and a pitch period p0 outside said range comprising determining the optimal tap weight for a single-tap predictor based on said input frame with a pitch period p0 and normalizing it to a range between 0 and 1, thereby forming a value W0N, determining the optimal tap weight for a single-tap predictor based on said input frame with a pitch period p1 and normalizing it to a range between 0 and 1, thereby forming a value W1N, when W1N is greater than or equal to a predetermined fraction of W0N, selecting then p1 is selected as the correct pitch estimate, otherwise p0 is selected as the correct pitch estimate.

Claim 26

The method of claim 25, wherein said predetermined fraction is substantially equal to 0.4. A method of pitch prediction for F-millisecond frames of sampled input signals comprising

Claim 27

The method of claim 11, wherein said step of making available filter parameters for said long-term filter comprises generating a first estimate of the pitch period from the current frame of input samples, generating a rounded representation, r, of said first estimate of the pitch period, generating a second estimate of the pitch period by the open-loop steps of performing an L-order LPC analysis of the signals in the input frame, performing an inverse LPC filtering of said input frame signals based on filter coefficients derived from said L-order analysis to determine a prediction residual signal, and extracting said second pitch period estimate by correlation peak picking of a function of said prediction residual signal, forming a difference signal representative of the difference between said second pitch period estimate and said rounded representation of said first estimate of the pitch period, when said difference signal has a magnitude greater than a preselected value, quantizing said difference signal into one of a plurality, q, of predetermined values, and forming a quantized value, p, for said pitch period in accordance with p=r + q, when said difference signal has a magnitude less than or equal to said preselected value, optimizing the quantization of said pitch period value in a closed loop quantization method.

Claim 28

The method of claim 27 wherein said generating a first estimate of said pitch period comprises forming an open-loop pitch prediction based on said input frame.

Claim 29

The method of claim 28 wherein said forming an open-loop pitch prediction comprises Determining whether said input frame comprises samples representative of voiced information, and when said input frame does not comprise input information that is voiced, setting said first estimate of said pitch period to a predetermined value.

Claim 30

The method of claim 29, wherein said setting said first estimate of said pitch period to a predetermined value comprises setting such value to a value between approximately 10% and 50% from the lower extremity of the expected range of the pitch periods.

Claim 31

The method of claim 11 wherein said deriving a pitch period comprises forming a first estimate of said pitch period using a prediction based on said input frame, forming a second estimate based on a prediction of the pitch period for the immediately preceding frame, forming a difference signal representing the difference between said first and second estimates, if said difference signal is greater than a predetermined value, quantizing said difference value to one of a fixed plurality of values to form a quantized difference signal, and deriving said pitch period from the sum of said second estimate and said quantized difference signal.

Claim 32

The method of claim 31, wherein said forming a second estimate comprises delaying the value of the predicted value for the immediately preceding frame, subtracting a fixed pitch bias value from said delayed value to yield a bias-adjusted value, adjusting the magnitude of said bias-adjusted value to from a magnitude-adjusted value, adding said fixed pitch bias value to said magnitude-adjusted value to form a predicted pitch period signal.

Claim 33

The method of claim 32, comprising the further step of rounding said predicted pitch period signal to form a rounded predicted pitch value.

Claim 34

The method of claim 13, wherein said deriving of filter parameters for said long-term filter comprises the steps of setting said filter parameters to fixed predetermined values not dependent on the particular values for the input signals when said frame of input signals does not represent voiced information.

Claim 35

The method of claim 34, wherein said deriving of filter parameters for said long-term filter comprises setting said pitch period parameter to a value between about 10% and 50% from the lower extremity of the expected range of values for the pitch period for input frames containing voiced information.

Claim 36

The method of claim 35, further comprising setting filter tap coefficients equal to a zero value when said frame of input signals does not represent voiced signals.