Abstract:
In a speech decoding method and apparatus, an adaptive code vector is obtained from an adaptive codebook, and a time series vector is obtained from an excitation codebook. Gains of the adaptive code vector and an excitation code vector are respectively decoded from a gain code. The gain of the adaptive code vector is classified into a first gain corresponding to a first noise level or a second gain corresponding to a second noise level. A value is determined based on the classifying results, and a mathematical operation is performed on the time series vector and the determined value. The adaptive code vector and the time series vector are weighted by the decoded gains, and an excitation signal is obtained by adding the weighted adaptive code vector and the weighted time series vector. A speech is synthesized using the excitation signal and a decoded linear prediction parameter.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a Divisional of application Ser. No. 11/976,841, filed on Oct. 29, 2007, now abandoned which is a Continuation of application Ser. No. 11/653,288, filed on Jan. 16, 2007, now U.S. Pat. No. 7,747,441 which is a divisional of application Ser. No. 11/188,624, filed on Jul. 26, 2005, now U.S. Pat. No. 7,383,177 which is a divisional of application Ser. No. 09/530,719 filed May 4, 2000 now U.S. Pat. No. 7,092,885, which is the national phase under 35 U.S.C. §371 of PCT International Application No. PCT/JP98/05513 having an international filing date of Dec. 7, 1998 and designating the United States of America and for which priority is claimed under 35 U.S.C. §120, said PCT International Application claiming priority under 35 U.S.C. §119(a) of Application No. 9-354754 filed in Japan on Dec. 24, 1997, the entire contents of all above-mentioned applications being incorporated herein by reference. 
    
    
     BACKGROUND OF THE INVENTION 
     (1) Field of the Invention 
     This invention relates to methods for speech coding and decoding and apparatuses for speech coding and decoding for performing compression coding and decoding of a speech signal to a digital signal. Particularly, this invention relates to a method for speech coding, method for speech decoding, apparatus for speech coding, and apparatus for speech decoding for reproducing a high quality speech at low bit rates. 
     (2) Description of Related Art 
     In the related art, code-excited linear prediction (Code-Excited Linear Prediction: CELP) coding is well-known as an efficient speech coding method, and its technique is described in “Code-excited linear prediction (CELP): High-quality speech at very low bit rates,” ICASSP &#39;85, pp. 937-940, by M. R. Shroeder and B. S. Atal in 1985 
       FIG. 6  illustrates an example of a whole configuration of a CELP speech coding and decoding method. In  FIG. 6 , an encoder  101 , decoder  102 , multiplexing means  103 , and dividing means  104  are illustrated. 
     The encoder  101  includes a linear prediction parameter analyzing means  105 , linear prediction parameter coding means  106 , synthesis filter  107 , adaptive codebook  108 , excitation codebook  109 , gain coding means  110 , distance calculating means  111 , and weighting-adding means  138 . The decoder  102  includes a linear prediction parameter decoding means  112 , synthesis filter  113 , adaptive codebook  114 , excitation codebook  115 , gain decoding means  116 , and weighting-adding means  139 . 
     In CELP speech coding, a speech in a frame of about 5-50 ms is divided into spectrum information and excitation information, and coded. 
     Explanations are made on operations in the CELP speech coding method. In the encoder  101 , the linear prediction parameter analyzing means  105  analyzes an input speech S 101 , and extracts a linear prediction parameter, which is spectrum information of the speech. The linear prediction parameter coding means  106  codes the linear prediction parameter, and sets a coded linear prediction parameter as a coefficient for the synthesis filter  107 . 
     Explanations are made on coding of excitation information. 
     An old excitation signal is stored in the adaptive codebook  108 . The adaptive codebook  108  outputs a time series vector, corresponding to an adaptive code inputted by the distance calculator  111 , which is generated by repeating the old excitation signal periodically. 
     A plurality of time series vectors trained by reducing distortion between speech for training and its coded speech, for example, is stored in the excitation codebook  109 . The excitation codebook  109  outputs a time series vector corresponding to an excitation code inputted by the distance calculator  111 . 
     Each of the time series vectors outputted from the adaptive codebook  108  and excitation codebook  109  is weighted by using a respective gain provided by the gain coding means  110  and added by the weighting-adding means  138 . Then, an addition result is provided to the synthesis filter  107  as excitation signals, and coded speech is produced. The distance calculating means  111  calculates a distance between the coded speech and the input speech S 101 , and searches an adaptive code, excitation code, and gains for minimizing the distance. When the above-stated coding is over, a linear prediction parameter code and the adaptive code, excitation code, and gain codes for minimizing a distortion between the input speech and the coded speech are outputted as a coding result. 
     Explanations are made on operations in the CELP speech decoding method. 
     In the decoder  102 , the linear prediction parameter decoding means  112  decodes the linear prediction parameter code to the linear prediction parameter, and sets the linear prediction parameter as a coefficient for the synthesis filter  113 . The adaptive codebook  114  outputs a time series vector corresponding to an adaptive code, which is generated by repeating an old excitation signal periodically. The excitation codebook  115  outputs a time series vector corresponding to an excitation code. The time series vectors are weighted by using respective gains, which are decoded from the gain codes by the gain decoding means  116 , and added by the weighting-adding means  139 . An addition result is provided to the synthesis filter  113  as an excitation signal, and an output speech S 103  is produced. 
     Among the CELP speech coding and decoding method, an improved speech coding and decoding method for reproducing a high quality speech according to the related art is described in “Phonetically—based vector excitation coding of speech at 3.6 kbps,” ICASSP &#39;89, pp. 49-52, by S. Wang and A. Gersho in 1989. 
       FIG. 7  shows an example of a whole configuration of the speech coding and decoding method according to the related art, and same signs are used for means corresponding to the means in  FIG. 6 . 
     In  FIG. 7 , the encoder  101  includes a speech state deciding means  117 , excitation codebook switching means  118 , first excitation codebook  119 , and second excitation codebook  120 . The decoder  102  includes an excitation codebook switching means  121 , first excitation codebook  122 , and second excitation codebook  123 . 
     Explanations are made on operations in the coding and decoding method in this configuration. In the encoder  101 , the speech state deciding means  117  analyzes the input speech S 101 , and decides a state of the speech is which one of two states, e.g., voiced or unvoiced. The excitation codebook switching means  118  switches the excitation codebooks to be used in coding based on a speech state deciding result. For example, if the speech is voiced, the first excitation codebook  119  is used, and if the speech is unvoiced, the second excitation codebook  120  is used. Then, the excitation codebook switching means  118  codes which excitation codebook is used in coding. 
     In the decoder  102 , the excitation codebook switching means  121  switches the first excitation codebook  122  and the second excitation codebook  123  based on a code showing which excitation codebook was used in the encoder  101 , so that the excitation codebook, which was used in the encoder  101 , is used in the decoder  102 . According to this configuration, excitation codebooks suitable for coding in various speech states are provided, and the excitation codebooks are switched based on a state of an input speech. Hence, a high quality speech can be reproduced. 
     A speech coding and decoding method of switching a plurality of excitation codebooks without increasing a transmission bit number according to the related art is disclosed in Japanese Unexamined Published Patent Application 8-185198. The plurality of excitation codebooks is switched based on a pitch frequency selected in an adaptive codebook, and an excitation codebook suitable for characteristics of an input speech can be used without increasing transmission data. 
     As stated, in the speech coding and decoding method illustrated in  FIG. 6  according to the related art, a single excitation codebook is used to produce a synthetic speech. Non-noise time series vectors with many pulses should be stored in the excitation codebook to produce a high quality coded speech even at low bit rates. Therefore, when a noise speech, e.g., background noise, fricative consonant, etc., is coded and synthesized, there is a problem that a coded speech produces an unnatural sound, e.g., “Jiri-Jiri” and “Chini-Chin.” This problem can be solved, if the excitation codebook includes only noise time series vectors. However, in that case, a quality of the coded speech degrades as a whole. 
     In the improved speech coding and decoding method illustrated in  FIG. 7  according to the related art, the plurality of excitation codebooks is switched based on the state of the input speech for producing a coded speech. Therefore, it is possible to use an excitation codebook including noise time series vectors in an unvoiced noise period of the input speech and an excitation codebook including non-noise time series vectors in a voiced period other than the unvoiced noise period, for example. Hence, even if a noise speech is coded and synthesized, an unnatural sound, e.g., “Jiri-Jiri,” is not produced. However, since the excitation codebook used in coding is also used in decoding, it becomes necessary to code and transmit data which excitation codebook was used. It becomes an obstacle for lowing bit rates. 
     According to the speech coding and decoding method of switching the plurality of excitation codebooks without increasing a transmission bit number according to the related art, the excitation codebooks are switched based on a pitch period selected in the adaptive codebook. However, the pitch period selected in the adaptive codebook differs from an actual pitch period of a speech, and it is impossible to decide if a state of an input speech is noise or non-noise only from a value of the pitch period. Therefore, the problem that the coded speech in the noise period of the speech is unnatural cannot be solved. 
     This invention was intended to solve the above-stated problems. Particularly, this invention aims at providing speech coding and decoding methods and apparatuses for reproducing a high quality speech even at low bit rates. 
     BRIEF SUMMARY OF THE INVENTION 
     In order to solve the above-stated problems, a speech decoding method is provided according to the present invention. The speech code to be decoded includes a linear prediction parameter code, an adaptive code, and a gain code. An adaptive code vector is obtained from an adaptive codebook based on the adaptive code. A time series vector is obtained from an excitation codebook. A gain of the adaptive code vector and a gain of an excitation code vector are decoded from the gain code. The gain of the adaptive code vector is classified into a first gain corresponding to a first noise level or a second gain corresponding to a second noise level, the first and second noise levels being different from one another. A value to be used in modifying the time series vector is determined based on the results of classifying the gain of the adaptive code vector. A mathematical operation is performed on the time series vector and another operand, the other operand being the determined value. The adaptive code vector and the time series vector are weighted using the decoded gains as weights, and an excitation signal is obtained by adding the weighted adaptive code vector and the weighted time series vector. A linear prediction parameter is decoded from the linear prediction parameter code. A speech is synthesized using the linear prediction parameter and the excitation signal. 
     A speech decoding apparatus is also provided according to the present invention which includes: an adaptive code vector obtaining unit for obtaining an adaptive code vector from an adaptive codebook based on the adaptive code; a time series vector obtaining unit for obtaining a time series vector from an excitation codebook; a gain decoding unit for decoding a gain of the adaptive code vector and a gain of an excitation code vector from the gain code; a classifying unit for classifying the gain of the adaptive code vector into a first gain corresponding to a first noise level or a second gain corresponding to a second noise level, the first and second noise levels being different from one another; a value determining unit for determining a value to be used in modifying the time series vector based on the results of classifying the gain of the adaptive code vector; a time series vector processing unit for performing a mathematical operation on the time series vector and another operand, the other operand being the determined value; a weighting unit for weighting the adaptive code vector and the time series vector using the decoded gains as weights; an excitation signal obtaining unit for obtaining an excitation signal by adding the weighted adaptive code vector and the weighted time series vector; a linear prediction parameter decoding unit for decoding a linear prediction parameter from the linear prediction parameter code; and a synthesizing unit for synthesizing a speech using the linear prediction parameter and the excitation signal. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a block diagram of a whole configuration of a speech coding and speech decoding apparatus in embodiment 1 of this invention; 
         FIG. 2  shows a table for explaining an evaluation of a noise level in embodiment 1 of this invention illustrated in  FIG. 1 ; 
         FIG. 3  shows a block diagram of a whole configuration of a speech coding and speech decoding apparatus in embodiment 3 of this invention; 
         FIG. 4  shows a block diagram of a whole configuration of a speech coding and speech decoding apparatus in embodiment 5 of this invention; 
         FIG. 5  shows a schematic line chart for explaining a decision process of weighting in embodiment 5 illustrated in  FIG. 4 ; 
         FIG. 6  shows a block diagram of a whole configuration of a CELP speech coding and decoding apparatus according to the related art; 
         FIG. 7  shows a block diagram of a whole configuration of an improved CELP speech coding and decoding apparatus according to the related art; and 
         FIG. 8  shows a block diagram of a whole configuration of a speech coding and decoding apparatus according to embodiment 8 of the invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Explanations are made on embodiments of this invention with reference to drawings. 
     Embodiment 1 
       FIG. 1  illustrates a whole configuration of a speech coding method and speech decoding method in embodiment 1 according to this invention. In  FIG. 1 , an encoder  1 , a decoder  2 , a multiplexer  3 , and a divider  4  are illustrated. The encoder  1  includes a linear prediction parameter analyzer  5 , linear prediction parameter encoder  6 , synthesis filter  7 , adaptive codebook  8 , gain encoder  10 , distance calculator  11 , first excitation codebook  19 , second excitation codebook  20 , noise level evaluator  24 , excitation codebook switch  25 , and weighting-adder  38 . The decoder  2  includes a linear prediction parameter decoder  12 , synthesis filter  13 , adaptive codebook  14 , first excitation codebook  22 , second excitation codebook  23 , noise level evaluator  26 , excitation codebook switch  27 , gain decoder  16 , and weighting-adder  39 . In  FIG. 1 , the linear prediction parameter analyzer  5  is a spectrum information analyzer for analyzing an input speech S 1  and extracting a linear prediction parameter, which is spectrum info illation of the speech. The linear prediction parameter encoder  6  is a spectrum information encoder for coding the linear prediction parameter, which is the spectrum information and setting a coded linear prediction parameter as a coefficient for the synthesis filter  7 . The first excitation codebooks  19  and  22  store pluralities of non-noise time series vectors, and the second excitation codebooks  20  and  23  store pluralities of noise time series vectors. The noise level evaluators  24  and  26  evaluate a noise level, and the excitation codebook switches  25  and  27  switch the excitation codebooks based on the noise level. 
     Operations are Explained. 
     In the encoder  1 , the linear prediction parameter analyzer  5  analyzes the input speech S 1 , and extracts a linear prediction parameter, which is spectrum informafion of the speech. The linear prediction parameter encoder  6  codes the linear prediction parameter. Then, the linear prediction parameter encoder  6  sets a coded linear prediction parameter as a coefficient for the synthesis filter  7 , and also outputs the coded linear prediction parameter to the noise level evaluator  24 . 
     Explanations are Made on Coding of Excitation Information. 
     An old excitation signal is stored in the adaptive codebook  8 , and a time series vector corresponding to an adaptive code inputted by the distance calculator  11 , which is generated by repeating an old excitation signal periodically, is outputted. The noise level evaluator  24  evaluates a noise level in a concerning coding period based on the coded linear prediction parameter inputted by the linear prediction parameter encoder  6  and the adaptive code, e.g., a spectrum gradient, short-term prediction gain, and pitch fluctuation as shown in  FIG. 2 , and outputs an evaluation result to the excitation codebook switch  25 . The excitation codebook switch  25  switches excitation codebooks for coding based on the evaluation result of the noise level. For example, if the noise level is low, the first excitation codebook  19  is used, and if the noise level is high, the second excitation codebook  20  is used. 
     The first excitation codebook  19  stores a plurality of non-noise time series vectors, e.g., a plurality of time series vectors trained by reducing a distortion between a speech for training and its coded speech. The second excitation codebook  20  stores a plurality of noise time series vectors, e.g., a plurality of time series vectors generated from random noises. Each of the first excitation codebook  19  and the second excitation codebook  20  outputs a time series vector respectively corresponding to an excitation code inputted by the distance calculator  11 . Each of the time series vectors from the adaptive codebook  8  and one of first excitation codebook  19  or second excitation codebook  20  are weighted by using a respective gain provided by the gain encoder  10 , and added by the weighting-adder  38 . An addition result is provided to the synthesis filter  7  as excitation signals, and a coded speech is produced. The distance calculator  11  calculates a distance between the coded speech and the input speech S 1 , and searches an adaptive code, excitation code, and gain for minimizing the distance. When this coding is over, the linear prediction parameter code and an adaptive code, excitation code, and gain code for minimizing the distortion between the input speech, and the coded speech are outputted as a coding result S 2 . These are characteristic operations in the speech coding method in embodiment 1. 
     Explanations are made on the decoder  2 . In the decoder  2 , the linear prediction parameter decoder  12  decodes the linear prediction parameter code to the linear prediction parameter, and sets the decoded linear prediction parameter as a coefficient for the synthesis filter  13 , and outputs the decoded linear prediction parameter to the noise level evaluator  26 . 
     Explanations are made on decoding of excitation information. The adaptive codebook  14  outputs a time series vector corresponding to an adaptive code, which is generated by repeating an old excitation signal periodically. The noise level evaluator  26  evaluates a noise level by using the decoded linear prediction parameter inputted by the linear prediction parameter decoder  12  and the adaptive code in a same method with the noise level evaluator  24  in the encoder  1 , and outputs an evaluation result to the excitation codebook switch  27 . The excitation codebook switch  27  switches the first excitation codebook  22  and the second excitation codebook  23  based on the evaluation result of the noise level in a same method with the excitation codebook switch  25  in the encoder  1 . 
     A plurality of non-noise time series vectors, e.g., a plurality of time series vectors generated by training for reducing a distortion between a speech for training and its coded speech, is stored in the first excitation codebook  22 . A plurality of noise time series vectors, e.g., a plurality of vectors generated from random noises, is stored in the second excitation codebook  23 . Each of the first and second excitation codebooks outputs a time series vector respectively corresponding to an excitation code. The time series vectors from the adaptive codebook  14  and one of first excitation codebook  22  or second excitation codebook  23  are weighted by using respective gains, decoded from gain codes by the gain decoder  16 , and added by the weighting-adder  39 . An addition result is provided to the synthesis filter  13  as an excitation signal, and an output speech S 3  is produced. These are operations are characteristic operations in the speech decoding method in embodiment 1. 
     In embodiment 1, the noise level of the input speech is evaluated by using the code and coding result, and various excitation codebooks are used based on the evaluation result. Therefore, a high quality speech can be reproduced with a small data amount. 
     In embodiment 1, the plurality of time series vectors is stored in each of the excitation codebooks  19 ,  20 ,  22 , and  23 . However, this embodiment can be realized as far as at least a time series vector is stored in each of the excitation codebooks. 
     Embodiment 2 
     In embodiment 1, two excitation codebooks are switched. However, it is also possible that three or more excitation codebooks are provided and switched based on a noise level. 
     In embodiment 2, a suitable excitation codebook can be used even for a medium speech, slightly noisy, in addition to two kinds of speech, i.e., noise and non-noise. Therefore, a high quality speech can be reproduced. 
     Embodiment 3 
       FIG. 3  shows a whole configuration of a speech coding method and speech decoding method in embodiment 3 of this invention. In  FIG. 3 , same signs are used for units corresponding to the units in  FIG. 1 . In  FIG. 3 , excitation codebooks  28  and  30  store noise time series vectors, and samplers  29  and  31  set an amplitude value of a sample with a low amplitude in the time series vectors to zero. 
     Operations are explained. In the encoder  1 , the linear prediction parameter analyzer  5  analyzes the input speech S 1 , and extracts a linear prediction parameter, which is spectrum information of the speech. The linear prediction parameter encoder  6  codes the linear prediction parameter. Then, the linear prediction parameter encoder  6  sets a coded linear prediction parameter as a coefficient for the synthesis filter  7 , and also outputs the coded linear prediction parameter to the noise level evaluator  24 . 
     Explanations are made on coding of excitation information. An old excitation signal is stored in the adaptive codebook  8 , and a time series vector corresponding to an adaptive code inputted by the distance calculator  11 , which is generated by repeating an old excitation signal periodically, is outputted. The noise level evaluator  24  evaluates a noise level in a concerning coding period by using the coded linear prediction parameter, which is inputted from the linear prediction parameter encoder  6 , and an adaptive code, e.g., a spectrum gradient, short-term prediction gain, and pitch fluctuation, and outputs an evaluation result to the sampler  29 . 
     The excitation codebook  28  stores a plurality of time series vectors generated from random noises, for example, and outputs a time series vector corresponding to an excitation code inputted by the distance calculator  11 . If the noise level is low in the evaluation result of the noise, the sampler  29  outputs a time series vector, in which an amplitude of a sample with an amplitude below a determined value in the time series vectors, inputted from the excitation codebook  28 , is set to zero, for example. If the noise level is high, the sampler  29  outputs the time series vector inputted from the excitation codebook  28  without modification. Each of the times series vectors from the adaptive codebook  8  and the sampler  29  is weighted by using a respective gain provided by the gain encoder  10  and added by the weighting-adder  38 . An addition result is provided to the synthesis filter  7  as excitation signals, and a coded speech is produced. The distance calculator  11  calculates a distance between the coded speech and the input speech S 1 , and searches an adaptive code, excitation code, and gain for minimizing the distance. When coding is over, the linear prediction parameter code and the adaptive code, excitation code, and gain code for minimizing a distortion between the input speech and the coded speech are outputted as a coding result S 2 . These are characteristic operations in the speech coding method in embodiment 3. 
     Explanations are made on the decoder  2 . In the decoder  2 , the linear prediction parameter decoder  12  decodes the linear prediction parameter code to the linear prediction parameter. The linear prediction parameter decoder  12  sets the linear prediction parameter as a coefficient for the synthesis filter  13 , and also outputs the linear prediction parameter to the noise level evaluator  26 . 
     Explanations are made on decoding of excitation information. The adaptive codebook  14  outputs a time series vector corresponding to an adaptive code, generated by repeating an old excitation signal periodically. The noise level evaluator  26  evaluates a noise level by using the decoded linear prediction parameter inputted from the linear prediction parameter decoder  12  and the adaptive code in a same method with the noise level evaluator  24  in the encoder  1 , and outputs an evaluation result to the sampler  31 . 
     The excitation codebook  30  outputs a time series vector corresponding to an excitation code. The sampler  31  outputs a time series vector based on the evaluation result of the noise level in same processing with the sampler  29  in the encoder  1 . Each of the time series vectors outputted from the adaptive codebook  14  and sampler  31  are weighted by using a respective gain provided by the gain decoder  16 , and added by the weighting-adder  39 . An addition result is provided to the synthesis filter  13  as an excitation signal, and an output speech S 3  is produced. 
     In embodiment 3, the excitation codebook storing noise time series vectors is provided, and an excitation with a low noise level can be generated by sampling excitation signal samples based on an evaluation result of the noise level the speech. Hence, a high quality speech can be reproduced with a small data amount. Further, since it is not necessary to provide a plurality of excitation codebooks, a memory amount for storing the excitation codebook can be reduced. 
     Embodiment 4 
     In embodiment 3, the samples in the time series vectors are either sampled or not. However, it is also possible to change a threshold value of an amplitude for sampling the samples based on the noise level. In embodiment 4, a suitable time series vector can be generated and used also for a medium speech, e.g., slightly noisy, in addition to the two types of speech, i.e., noise and non-noise. Therefore, a high quality speech can be reproduced. 
     Embodiment 5 
       FIG. 4  shows a whole configuration of a speech coding method and a speech decoding method in embodiment 5 of this invention, and same signs are used for units corresponding to the units in  FIG. 1 . 
     In  FIG. 4 , first excitation codebooks  32  and  35  store noise time series vectors, and second excitation codebooks  33  and  36  store non-noise time series vectors. The weight determiners  34  and  37  are also illustrated. 
     Operations are explained. In the encoder  1 , the linear prediction parameter analyzer  5  analyzes the input speech S 1 , and extracts a linear prediction parameter, which is spectrum information of the speech. The linear prediction parameter encoder  6  codes the linear prediction parameter. Then, the linear prediction parameter encoder  6  sets a coded linear prediction parameter as a coefficient for the synthesis filter  7 , and also outputs the coded prediction parameter to the noise level evaluator  24 . 
     Explanations are made on coding of excitation information. The adaptive codebook  8  stores an old excitation signal, and outputs a time series vector corresponding to an adaptive code inputted by the distance calculator  11 , which is generated by repeating an old excitation signal periodically. The noise level evaluator  24  evaluates a noise level in a concerning coding period by using the coded linear prediction parameter, which is inputted from the linear prediction parameter encoder  6  and the adaptive code, e.g., a spectrum gradient, short-term prediction gain, and pitch fluctuation, and outputs an evaluation result to the weight determiner  34 . 
     The first excitation codebook  32  stores a plurality of noise time series vectors generated from random noises, for example, and outputs a time series vector corresponding to an excitation code. The second excitation codebook  33  stores a plurality of time series vectors generated by training for reducing a distortion between a speech for training and its coded speech, and outputs a time series vector corresponding to an excitation code inputted by the distance calculator  11 . The weight determiner  34  determines a weight provided to the time series vector from the first excitation codebook  32  and the time series vector from the second excitation codebook  33  based on the evaluation result of the noise level inputted from the noise level evaluator  24 , as illustrated in  FIG. 5 , for example. Each of the time series vectors from the first excitation codebook  32  and the second excitation codebook  33  is weighted by using the weight provided by the weight determiner  34 , and added. The time series vector outputted from the adaptive codebook  8  and the time series vector, which is generated by being weighted and added, are weighted by using respective gains provided by the gain encoder  10 , and added by the weighting-adder  38 . Then, an addition result is provided to the synthesis filter  7  as excitation signals, and a coded speech is produced. The distance calculator  11  calculates a distance between the coded speech and the input speech S 1 , and searches an adaptive code, excitation code, and gain for minimizing the distance. When coding is over, the linear prediction parameter code, adaptive code, excitation code, and gain code for minimizing a distortion between the input speech and the coded speech, are outputted as a coding result. 
     Explanations are made on the decoder  2 . In the decoder  2 , the linear prediction parameter decoder  12  decodes the linear prediction parameter code to the linear prediction parameter. Then, the linear prediction parameter decoder  12  sets the linear prediction parameter as a coefficient for the synthesis filter  13 , and also outputs the linear prediction parameter to the noise evaluator  26 . 
     Explanations are made on decoding of excitation information. The adaptive codebook  14  outputs a time series vector corresponding to an adaptive code by repeating an old excitation signal periodically. The noise level evaluator  26  evaluates a noise level by using the decoded linear prediction parameter, which is inputted from the linear prediction parameter decoder  12 , and the adaptive code in a same method with the noise level evaluator  24  in the encoder  1 , and outputs an evaluation result to the weight determiner  37 . 
     The first excitation codebook  35  and the second excitation codebook  36  output time series vectors corresponding to excitation codes. The weight determiner  37  weights based on the noise level evaluation result inputted from the noise level evaluator  26  in a same method with the weight determiner  34  in the encoder  1 . Each of the time series vectors from the first excitation codebook  35  and the second excitation codebook  36  is weighted by using a respective weight provided by the weight determiner  37 , and added. The time series vector outputted from the adaptive codebook  14  and the time series vector, which is generated by being weighted and added, are weighted by using respective gains decoded from the gain codes by the gain decoder  16 , and added by the weighting-adder  39 . Then, an addition result is provided to the synthesis filter  13  as an excitation signal, and an output speech S 3  is produced. 
     in embodiment 5, the noise level of the speech is evaluated by using a code and coding result, and the noise time series vector or non-noise time series vector are weighted based on the evaluation result, and added. Therefore, a high quality speech can be reproduced with a small data amount. 
     Embodiment 6 
     In embodiments 1-5, it is also possible to change gain codebooks based on the evaluation result of the noise level. In embodiment 6, a most suitable gain codebook can be used based on the excitation codebook. Therefore, a high quality speech can be reproduced. 
     Embodiment 7 
     In embodiments 1-6, the noise level of the speech is evaluated, and the excitation codebooks are switched based on the evaluation result. However, it is also possible to decide and evaluate each of a voiced onset, plosive consonant, etc., and switch the excitation codebooks based on an evaluation result. In embodiment 7, in addition to the noise state of the speech, the speech is classified in more details, e.g., voiced onset, plosive consonant, etc., and a suitable excitation codebook can be used for each state. Therefore, a high quality speech can be reproduced. 
     Embodiment 8 
     In embodiments 1-6, the noise level in the coding period is evaluated by using a spectrum gradient, short-term prediction gain, pitch fluctuation. However, it is also possible to evaluate the noise level by using a ratio of a gain value against an output from the adaptive codebook as illustrated in  FIG. 8 , in which similar elements are labeled with the same reference numerals. 
     INDUSTRIAL APPLICABILITY 
     In the speech coding method, speech decoding method, speech coding apparatus, and speech decoding apparatus according to this invention, a noise level of a speech in a concerning coding period is evaluated by using a code or coding result of at least one of the spectrum information, power information, and pitch information, and various excitation codebooks are used based on the evaluation result. Therefore, a high quality speech can be reproduced with a small data amount. 
     In the speech coding method and speech decoding method according to this invention, a plurality of excitation codebooks storing excitations with various noise levels is provided, and the plurality of excitation codebooks is switched based on the evaluation result of the noise level of the speech. Therefore, a high quality speech can be reproduced with a small data amount. 
     In the speech coding method and speech decoding method according to this invention, the noise levels of the time series vectors stored in the excitation codebooks are changed based on the evaluation result of the noise level of the speech. Therefore, a high quality speech can be reproduced with a small data amount. 
     In the speech coding method and speech decoding method according to this invention, an excitation codebook storing noise time series vectors is provided, and a time series vector with a low noise level is generated by sampling signal samples in the time series vectors based on the evaluation result of the noise level of the speech. Therefore, a high quality speech can be reproduced with a small data amount. 
     In the speech coding method and speech decoding method according to this invention, the first excitation codebook storing noise time series vectors and the second excitation codebook storing non-noise time series vectors are provided, and the time series vector in the first excitation codebook or the time series vector in the second excitation codebook is weighted based on the evaluation result of the noise level of the speech, and added to generate a time series vector. Therefore, a high quality speech can be reproduced with a small data amount.