Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission
Reexamination Certificate
2000-07-25
2002-10-15
McFadden, Susan (Department: 2654)
Data processing: speech signal processing, linguistics, language
Speech signal processing
For storage or transmission
C704S225000, C704S206000, C704S208000
Reexamination Certificate
active
06466904
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to digital voice decoding and, more particularly, to a method and apparatus for using harmonic modeling in an improved speech decoder.
BACKGROUND OF THE INVENTION
A general diagram of a CELP encoder
100
is shown in
FIG. 1
A. A CELP encoder uses a model of the human vocal tract in order to reproduce a speech input signal. The parameters for the model are actually extracted from the speech signal being reproduced, and it is these parameters that are sent to a decoder
112
, which is illustrated in FIG.
1
A. Decoder
112
uses the parameters in order to reproduce the speech signal. Referring to
FIG. 1A
, synthesis filter
104
is a linear predictive filter and serves as the vocal tract model for CELP encoder
100
. Synthesis filter
104
takes an input excitation signal &mgr;(n) and synthesizes a speech signal s(n) by modeling the correlations introduced into speech by the vocal tract and applying them to the excitation signal &mgr;(n).
In CELP encoder
100
speech is broken up into frames, usually 20 ms each, and parameters for synthesis filter
104
are determined for each frame. Once the parameters are determined, an excitation signal &mgr;(n) is chosen for that frame. The excitation signal is then synthesized, producing a synthesized speech signal s′(n). The synthesized frame s′(n) is then compared to the actual speech input frame s(n) and a difference or error signal e(n) is generated by subtractor
106
. The subtraction function is typically accomplished via an adder or similar functional component as those skilled in the art will be aware. Actually, excitation signal &mgr;(n) is generated from a predetermined set of possible signals by excitation generator
102
. In CELP encoder
100
, all possible signals in the predetermined set are tried in order to find the one that produces the smallest error signal e(n). Once this particular excitation signal &mgr;(n) is found, the signal and the corresponding filter parameters are sent to decoder
112
(FIG.
1
B), which reproduces the synthesized speech signal s′(n). Signal s′(n) is reproduced in decoder
112
by using an excitation signal &mgr;(n), as generated by decoder excitation generator
114
, and synthesizing it using decoder synthesis filter
116
.
By choosing the excitation signal that produces the smallest error signal e(n), a very good approximation of speech inputs(n) can be reproduced in decoder
112
. The spectrum of error signal e(n), however, will be very flat, as illustrated by curve
204
in FIG.
2
. The flatness can create problems in that the signal-to-noise ratio (SNR), with regard to synthesized speech signal s′(n) (curve
202
), may become too small for effective reproduction of speech signal s(n). This problem is especially prevalent in the higher frequencies where, as illustrated in
FIG. 2
, there is typically less energy in the spectrum of s′(n). In order to combat this problem, CELP encoder
100
includes a feedback path that incorporates error weighting filter
108
. The function of error weighting filter
108
is to shape the spectrum of error signal e(n) so that the noise spectrum is concentrated in areas of high voice content. In effect, the shape of the noise spectrum associated with the weighted error signal e
w
(n) tracks the spectrum of the synthesized speech signal s′(n), as illustrated in
FIG. 2
by curve
206
. In this manner, the SNR is improved and the quality of the reproduced speech is increased.
In encoder
100
and decoder
112
, the vocal tract model works by assuming that speech signal s(n) remains constant for short periods of time. Speech signal s(n) is not constant, however, and because speech signal s(n) (curve
302
in
FIG. 3
) is actually changing all the time, noise is induced in the quantized speech signal &mgr;(n). As a result, the spectrum (curve
304
in
FIG. 3
) for quantized speech signal &mgr;(n) is not as smooth or periodic as the spectrum for speech signal s(n). The result is that synthesized speech signal s′(n) (curve
306
in FIG.
3
), in decoder
112
, produces noisy speech that does not sound as good as the actual speech signal s(n). Ideally, the synthesized speech would sound very close to the actual speech, and thus provide a good listening experience.
SUMMARY OF THE INVENTION
There is provided a speech decoder comprising a means for generating an excitation signal and a means for performing harmonic analysis and synthesis on the excitation signal in order to generate a smooth, periodic speech signal. The speech decoder further comprises a mixing means for mixing the excitation signal with the smooth, periodic signal and a synthesizing means for synthesizing the modified excitation signal into a speech signal that can be played to a user through a listening means.
There is also provided a receiver that incorporates a speech decoder such as the decoder described above as well as a method for speech decoding. These and other embodiments as well as further features and advantages of the invention are described in detail below.
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patent: 5701390 (1997-12-01), Griffin et al.
patent: 5754974 (1998-05-01), Griffin et al.
patent: 5890115 (1999-03-01), Cole
patent: 5907822 (1999-05-01), Prieto, Jr.
patent: 5946651 (1999-08-01), Jarvinen et al.
patent: 6029128 (2000-02-01), Jarvinen et al.
patent: 6233550 (2001-05-01), Gersho et al.
patent: 6377915 (2002-04-01), Sasaki
patent: 6418408 (2002-07-01), Bhaskar et al.
Gao Yang
Su Huan-yu
Conexant Systems Inc.
Farjami & Farjami LLP
McFadden Susan
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