Patent Publication Number: US-2005125394-A1

Title: Information search apparatus, information search method, and information recording medium on which information search program is recorded

Description:
BACKGROUND OF THE INVENTION  
      1. Field of the Invention  
      The present invention relates to an information search apparatus, an information search method, and an information recording medium on which an information search program is computer-readably recorded, and more particularly to a song search apparatus and a song search method in which one song or a plurality of songs comprised of lyrics and performances (prelude, accompaniment, interlude, and postlude; hereinafter, ‘prelude, accompaniment, interlude, and postlude’ referred to as ‘performance’) are searched, and an information recording medium on which a song search program is computer-readably recorded.  
      2. Related Art  
      Recently, digital data for reproducing a plurality of songs are stored by an onboard navigation apparatus or a home server apparatus or the like, and favorite songs among them are selected and reproduced.  
      At this time, in prior arts, as a first song search method, it is common that part of constituent words (phrases) constituting lyrics included in a song to be reproduced is inputted as it is and the song having lyrics including the constituent words is searched and reproduced.  
      Further, US 2003 078919 A1 (FIGS.  1  to  3 ) discloses a second song search method reflecting subjective feeling of a user. There is a search method for preparing a sensitivity table which can be updated with a correlation value between a search keyword (for example, cheerful music or refreshing music) and a feature word (for example, cheerfulness or energetic), preparing each feature word list representing ‘1’ and ‘0’ depending on whether or not there is a feature related to the feature word, and searching a plurality of matched songs on the basis of the sensitivity table and the feature word list when the user inputs a desired search keyword.  
      However, according to the above-mentioned conventional song search methods, there are the following prevalent problems. First, in the first song search method, there is a problem in that different search routines are performed for search words which are closely related to each other such as ‘coast’, ‘waterside’, and ‘beach’, respectively, and that an entirely different songs are searched for each of the words constituting lyrics in some cases. In addition, the search process is not efficient.  
      On the other hand, according to the second song search method, there is a problem in that appropriate songs are not searched since the sensitivity table is used with respect to only a search keyword inputted by a user and thus the correlation to the song to be searched is not taken into consideration.  
     SUMMARY OF THE INVENTION  
      Accordingly, the present invention is made in consideration of the above-mentioned problems, and an object of the present invention is to provide a song search apparatus and a song search method in which songs matched with the subjective feeling of a user can be quickly searched, a program for searching song, and an information recording medium in which the program for searching song is recorded.  
      The present invention will be described below. Although reference numerals in the accompanying drawings will be accessorily written as parenthetic numerals for descriptive convenience, the present invention is not limited to the illustrated features.  
      The above object of the present invention can be achieved by an information search apparatus (S) which searches one or plural songs among a plurality of songs comprised of lyrics and performances. The information search apparatus (S) is provided with: a song feature information storing device ( 3 ) which distinguishably stores song feature information comprised of constituent word information which indicates contents of a plurality of constituent words included in the song, and first sound feature information which indicates the sound feature of the performance included in the song, for every song; a search word input device ( 9 ) which is used to input a search word representing the song to be searched; a search word feature information storing device ( 4 ) which distinguishably stores, as search word feature information characterizing an inputted search word, the search word feature information comprised of first lyric feature information, which is a collection of weighted constituent words obtained by applying a weight value to each constituent word constituting the lyrics included in any one of the songs to be searched by using the search word, and second sound feature information which indicates sound feature of the performance included in any one of the songs to be searched by using the search word, for every search word; a comparison device ( 8 ) which compares input search word feature information as the search word feature information corresponding to the inputted search word with each of the stored first sound feature information; and an extracting device ( 8 ) which extracts songs to have the best similarity to the input search word feature information, as the songs corresponding to the inputted search word, based on the comparison result of the comparison device ( 8 ).  
      The above object of the present invention can be achieved by an information search method which searches one or plural songs among a plurality of songs comprised of lyrics and performances. The information search method is provided with: a search word input process in which a search word indicating a song to be searched is inputted; a comparison process in which, as input search word feature information characterizing an inputted search word, the input search word feature information comprised of first lyric feature information, which is a collection of weighted constituent words obtained by applying a weight value to each of the constituent words constituting the lyrics included in any one of the songs to be searched by using the inputted search word, and second sound feature information, which indicates sound feature of the performance included in any one of the songs to be searched by using the inputted search word, is compared with a plurality of entities of the first sound feature information which indicates the sound feature of the song included in each of the songs; and an extracting process in which songs to have the best similarity to the input search word feature information are extracted, as the songs which are appropriate for the inputted search word, based on the comparison result of the comparison process.  
      The above object of the present invention can be achieved by an information recording medium on which an information search program is recorded so as to be readable through a computer which is included in an information search apparatus (S) which searches one or plural songs among a plurality of songs comprised of lyrics and performances with a pre-installed re-writable recording medium. The information search program causes the computer to function as: a song feature information storing device ( 3 ) which distinguishably stores song feature information comprised of constituent word information that represents contents of a plurality of constituent words included in the song and first sound feature information which indicates the sound feature of the performance included in the song, for every song; a search word input device ( 9 ) which is used to input a search word representing the song to be searched; a search word feature information storing device ( 4 ) which distinguishably stores, as search word feature information characterizing an inputted search word, the search word feature information comprised of first lyric feature information which is a collection of weighted constituent words obtained by applying a weight value to each constituent word constituting the lyrics included in any one of the songs to be searched by using a corresponding search word and second sound feature information indicating the sound feature of the performance included in any one of the songs to be searched by using the corresponding search word, for every search word; a comparison device ( 8 ) which compares input search word feature information as the search word feature information corresponding to the inputted search word with each entity of the stored first sound feature information; and an extracting device ( 8 ) which extracts the songs to have the best similarity to the input search word feature information, as the songs appropriate for the inputted search word, based on the comparison result of the comparison device ( 8 ). 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       FIG. 1  is a block diagram showing a schematic configuration of a song search apparatus related to an embodiment of the present invention;  
       FIG. 2  illustrates the data structure of the information stored in the song search apparatus related to the embodiment, wherein  FIG. 2A  illustrates the data structure of song feature information,  FIG. 2B  illustrates the data structure of search word feature information, and  FIG. 2C  illustrates the order of performing when all modifications are simultaneously performed;  
       FIG. 3  is a flow chart showing a song search process related to the embodiment;  
       FIG. 4  illustrates a conversion table related to the embodiment;  
       FIG. 5  illustrates the data structure of history information related to the embodiment, wherein  FIG. 5A  illustrates a data structure of matching history information and  FIG. 5B  illustrates a data structure of non-matching history information;  
       FIG. 6  is a flow chart showing in detail a process of updating the conversion table;  
       FIG. 7  illustrates a specific example (I) of the process of updating the conversion table; and  
       FIG. 8  illustrates a concrete example (II) of the process of updating the conversion table. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS  
      Hereinafter, best embodiments of the present invention will now be described with reference to the drawings. Also, the below-mentioned embodiment is a case in which the present invention is applied to a song search apparatus for storing a plurality of songs and searching and outputting (reproducing) any one of songs according to a request of a user.  
      (I) Overall Configuration and Whole Operation  
      First, the overall configuration and the whole operation of the song search apparatus according to the present embodiment will be explained with reference to  FIGS. 1 and 2 . In addition,  FIG. 1  is a block diagram showing the schematic configuration of the song search apparatus, and  FIG. 2  illustrates the data structure of information accumulated in the song search apparatus.  
      As shown in  FIG. 1 , the song search apparatus S according to the present embodiment comprises a song input unit  1 , a song database  2  as a song storing device, a song feature information database  3  as a song feature information storing device, a search word feature information database  4  as a search word feature information storing device, a sound feature information extracting unit  5 , a constituent word information extracting unit  6 , a song feature information generating unit  7 , a search process unit  8  as a comparison device, an extracting device, a lyric feature information generating device, a table updating device, and a search word feature information updating device, an input unit  9  as a search word input device, an evaluation information input device, a song output unit  10 , and a history storage unit  11 .  
      At this time, in the song database  2 , a plurality of songs are accumulated and stored as an object to be searched by the below-mentioned song search process. Further, each of the songs is comprised of at least lyrics and a performance including prelude, accompaniment, interlude, and postlude.  
      Here, a song which is desired to be accumulated is inputted into the song database  2 , when song information Ssg corresponding to the song is inputted into the song input unit  1  from the outside, by performing the format conversion process etc. for storing the song information Ssg in the song database  2  at the song input unit  1  to input the processed song information Ssg into the song database  2 .  
      Next, the song feature information database  3  is accumulated with song feature information corresponding to all the songs accumulated in the song database  2  such that the song feature information can be identified with respect to each of the songs.  
      Here, the song feature information is accumulated in the song feature information database  3  such that it corresponds to each of all the songs accumulated in the song database  2 , and is the information characterizing the respective lyrics and performance of each of the songs.  
      Next, the song feature information will be explained with reference to  FIGS. 1 and 2 A.  
      When a new song is inputted into the song database  2  as song information Ssg, the song feature information is newly generated in accordance with the song and the generated song feature information is newly registered and accumulated in the song feature information database  3 .  
      Here, when a new song is accumulated in the song database  2 , the song information Ssg corresponding to the song is read from the song database  2  and is outputted to the sound feature information extracting unit  5  and the constituent word information extracting unit  6 , as shown in  FIG. 1 .  
      Further, a plurality of parameters representing the sound feature of the song are extracted from the song information Ssg and are outputted to the song feature information generating unit  7  as sound feature information Sav by the sound feature information extracting unit  5 .  
      At this time, as the plurality of parameters included in the sound feature information Sav, there are, as shown in the right side of  FIG. 2A , for example, a speed (BPM (Beet Per Minutes)) of the song, a maximum output level of the song (maximum sound volume), an average output level of the song (average sound volume), a code included in the song, a beat level of the song (that is, the signal level (magnitude) of the beat component of the song), and the key of the song (C major or A minor).  
      In parallel to the above, the constituent word information extracting unit  6  extracts lyrics (words of the song) included in the song from the song information Ssg, searches whether or not the constituent words (phrases, hereinafter referred to simply as constituent words) set previously in the extracted lyrics are included, generates the constituent word feature information Swd for each of the constituent words indicating the search result (regarding whether or not the constituent words are included in the lyrics), and outputs them to the song feature information generating unit  7 .  
      At this time, the constituent word feature information Swd shows whether or not the constituent words set previously such as ‘love’, ‘sea’, ‘thought’, or ‘hope’ are included in lyrics constituting a song. When the constituent word is included in the lyrics, the value of the constituent word feature information Swd for the constituent word is defined to be ‘1’, and, when the constituent word is not included in the lyrics, the value of the constituent word feature information Swd for the constituent word is defined to be ‘0’. More specifically, for example, as shown in the left side of  FIG. 2A , the song having the song number ‘0’ in the song database  2  includes the constituent word ‘love’, but does not include the constituent words ‘sea’, ‘thought’, and ‘hope’.  
      Thereby, the song feature information generating unit  7  combines the sound feature information Sav and the corresponding constituent word feature information Swd for every song, outputs the song feature information Ssp composed of a plurality of entities of song feature information  20  corresponding to each of the songs to the song feature information database  3 , as shown in  FIG. 2A , and registers and accumulates it in the song feature information database  3 . At this time, as shown in  FIG. 2A , the song feature information  20  of one song is comprised of the sound feature extracted from the song by the sound feature information extracting unit  5  and the constituent word information extracted from the lyrics of the song by the constituent word information extracting unit  6 .  
      In addition, the search word feature information corresponding to the whole search words previously set as search keywords (that is, the search keywords subjectively characterizing the song which a user wants to listen to at that time, hereinafter, referred to simply as the search words) inputted by the user in the below-mentioned song search process is distinguishably accumulated in the search word feature information database  4  for each of the search words.  
      Here, the search word feature information must be selected and inputted when a user searches songs from the songs accumulated in the song database  2 , and it is the information characterizing each of the search words inputted by the user.  
      In the above embodiment, the constituent word information extracting unit  6  searches whether or not the constituent words set previously in the lyrics extracted from the song information Ssg, generates the constituent word feature information Swd for each of the constituent words, and outputs them to the song feature information generating unit  7 . However, the constituent word feature information Swd can be generated in other modified ways as follows: More specifically, in the case that images of a constitution word can be changeable by its adjacent modifier, the meanings of the constitution word can be analyzed in consideration of the changed images, and the constituent word feature information Swd can be generated. In addition, on the basis of the normalized appearance numbers obtained by dividing the appearance numbers of the constitution word in one song with the length of the whole lyrics, the constituent word feature information Swd can be generated. Further, on the basis of a constitution word used in a title of a song, the constituent word feature information Swd can be generated. In this case, the constitution words of the song title can be assigned different weights to from ones to constitution words of lyrics in a song. Furthermore, by getting constitution words grouped by use of a thesaurus database (not shown), the constituent word feature information Swd can be generated on the basis of appearance numbers of each group to which a constitution word belongs. When lyrics in a song contain constitution words in different languages (such as English, French, German, Spanish, and Japanese), the constituent word feature information Swd can be generated on the basis of appearance numbers of each of the constitution words in the different language. Further, in the above-mentioned explanation, depending on whether or not the constituent words set previously are included in lyrics constituting a song, the value of the constituent word feature information Swd for the constituent word is defined to be ‘1’ or ‘0’, or binarized. However, the appearance numbers of the constituent words in a song are counted. When the counted appearance numbers are equal to or over a predetermined threshold, the value of the constituent ward feature information Swd for the constituent word can be defined to be ‘1’, and when the counted appearance numbers are less than the threshold, the value of the constituent word feature information Swd can be defined to be ‘0’. These modifications of generating the constituent word feature information can be performed independently each other and can be simultaneously performed together with all modifications. When all modifications are simultaneously performed, these modifications are performed in an order shown in  FIG. 2C .  
      Next, the search word feature information will be explained with reference to  FIG. 2B  in detail.  
      As shown in  FIG. 2B , one entity of search word feature information  30  comprises search word feature information identifying information (shown by ‘search ID’ in  FIG. 2B ) for identifying each of the search word feature information  30  from other entities of the search word feature information  30 , a search word itself corresponding to the search word feature information  30 , lyric feature information characterizing lyrics included in a song to be searched and extracted (in other words, expected to be searched and extracted) from the song database  2  by using the corresponding search word, and sound feature information including the plurality of parameters representing the sound feature of the song to be searched and extracted.  
      Here, the sound feature information constituting the search word feature information  30  specifically includes sound parameters similar to those parameters included in the sound feature information Sav.  
      Also, similarly, the lyric feature information constituting the search word feature information  30  is a collection composed by applying a weight value to each of the plurality of subjective pieces of the lyric feature information characterizing the lyrics included in the song to be searched and extracted by using the search word feature information  30 , according to the specific content of the respective lyrics included in the song to be searched and extracted by using the search word corresponding to the search word feature information  30 .  
      More specifically, as shown in  FIG. 2B , with respect to the search word feature information  30  corresponding to the search word ‘heart-warming’, the lyric feature information of ‘heart-warming’ is formed with the weight value of 0.9 against the other lyric feature information, the lyric feature information of ‘heartening’ is formed with the weight value of 0.3 against the other lyric feature information, the lyric feature information of ‘sad, lonely’ is formed with the weight value of 0.1 against the other lyric feature information, and the lyric feature information of ‘cheerful’ is formed with the weight value of 0 against the other lyric feature information. On the other hand, with respect to the search word feature information  30  corresponding to the search word of ‘cheerful’, the lyric feature information of ‘cheerful’ is formed with the weight value of 0.7 against the other lyric feature information, the lyric feature information of ‘heart-warming’ is formed with the weight value of 0.2 against the other lyric feature information, the lyric feature information of ‘heartening’ is formed with the weight value of 0.5 against the other lyric feature information, and the lyric feature information of ‘sad, lonely’ is formed with the weight value of 0 against the other lyric feature information. Also, with respect to the search word feature information  30  corresponding to the search word of ‘sad, lonely’, the lyric feature information of ‘heart-warming’ is formed with the weight value of 0.3 against the other lyric feature information, the lyric feature information of ‘sad, lonely’ is formed with the weight value of 0.8 against the other lyric feature information, and the lyric feature information of ‘cheerful’ and ‘heartening’ is formed with the weight value of 0 against the other lyric feature information. Further, with respect to the search word feature information  30  corresponding to the search word of ‘heartening’ or ‘quiet’, each of the lyric feature information of ‘heart-warming’, ‘cheerful’, ‘sad, lonely’ and ‘heartening’ is formed with a predetermined weight value.  
      Moreover, as mentioned below, in order to obtain the search result of favorite songs of a user, the same subjective concept as the subjective concept represented by each of the lyric feature information is represented by any one of the search words. Also, each of the lyric feature information itself represents the feature of the songs (more specifically, the lyrics included in the song) accumulated in the song database  2  but is independent from the search word itself. The detailed description thereof will be mentioned below.  
      Also, in case a user subjectively searches a desired song by using the information accumulated in the song feature information database  3  and the search word feature information database  4 , after any search word is inputted at the input unit  9  by the user, input information Sin representing the inputted search word is outputted to the search process unit  8 .  
      Thereby, the search process unit  8  extracts one entity of the search word feature information  30  corresponding to the inputted search word from the search word feature information database  4  as search word feature information Swds on the basis of the input information Sin, and simultaneously extracts a plurality of entities of the song feature information  20  corresponding to the entire songs accumulated in the song database  2  from the song feature information database  3  as song feature information Ssp. Then, the extracted entity of the search word feature information  30  is compared with those of the song feature information  20 , and song identifying information Srz representing the songs corresponding to the entities of the song feature information  20  which have the best similarity to the entity of the search word feature information  30  are generated and outputted to the song database  2 .  
      Thereby, the song database  2  outputs the song represented by the song identifying information Srz to the song output unit  10  as song information Ssg.  
      Then, the song output unit  10  performs an output interface process etc. needed for the output song information Ssg and outputs the processed song information Ssg to an external amplifier unit or a broadcasting unit or the like (not shown).  
      Also, after the song information Ssg representing one song is outputted from the song output unit  10 , evaluation information regarding whether or not the song corresponding to the outputted song information Ssg is appropriate for a song required by a user who initially inputs a search word, is again inputted into the input unit  9 , and the corresponding input information Sin is outputted to the search process unit  8 .  
      Thereby, the search process unit  8  generates history information representing the result of the past song search process on the basis of the evaluation information inputted as the input information Sin, and temporarily stores history information Sm in the history storage unit  11  and reads out it if necessary to perform the below-mentioned history managing process.  
      (II) Song Search Process  
      Next, the song search process related to the embodiment performed by using the song search apparatus S comprising the above-mentioned configuration will be explained with reference to FIGS.  3  to  8  in detail. In addition,  FIG. 3  is a flow chart showing the song search process in the song search apparatus,  FIG. 4  illustrates the content of a conversion table used in the song search process,  FIG. 5  illustrates the history information used in the history process related to the embodiment,  FIG. 6  is a flow chart showing the history managing process of the history information, and  FIGS. 7 and 8  illustrate databases used in the history managing process.  
      As shown in  FIG. 3 , in the song search process performed on the basis of the search process unit  8 , when a desired subjective search word is initially determined and inputted by a user into the input unit  9  (step S 1 ), the entity of the search word feature information  30  corresponding to the inputted search word is extracted from the search word feature information database  4  and is outputted to the search process unit  8  (step S 2 ).  
      In addition, in parallel with the process of the steps S 1  and S 2 , for every song, the constituent words constituting the lyrics included in the entire songs are read from the song feature information database  3  and then outputted to the search process unit  8  (step S 3 ). Then, for every song, the search process unit  8  performs the process for converting the constituent words into the lyric feature information corresponding to the lyric included in each song by using the conversion table stored in the memory (not shown) in the search process unit  8  (step S 4 ).  
      Here, the conversion table will be explained with reference to  FIG. 4  in detail.  
      The lyric feature information generated by the process of the step S 4  is identical to the lyric feature information with the weight values included in the search word feature information  30 , and is a collection composed by applying the weight value to each of the constituent words constituting the lyrics included in the song according to the specific content of each lyric feature information, for every song corresponding to the lyric feature information.  
      More specifically, in the example of the conversion table T shown in  FIG. 4 , with respect to lyric feature information  40  of ‘heart-warming’, the constituent word of ‘hope’ is formed with the weight value of 0.4 against the other constituent words, the constituent words of ‘sea’ and ‘thought’ are formed with the weight value of 0.1 against the other constituent words, the constituent word of ‘love’ is formed with the weight value of 0 against the other constituent words, and thus the lyric feature information of ‘heart-warming’ is generated. With respect to the lyric feature information  40  of ‘cheerful’, the constituent word of ‘thought’ is formed with the weight value of 0.8 against the other constituent words, the constituent word of ‘love’ is formed with the weight value of 0.2 against the other constituent words, and the constituent words of ‘sea’ and ‘hope’ are formed with the weight value of 0.1 against the other constituent words. With respect to the lyric feature information  40  of ‘sad, lonely’, the constituent word of ‘hope’ is formed with the weight value of 0.7 against the other constituent words, the constituent word of ‘sea’ is formed with the weight value of 0.2 against the other constituent words, the constituent words of ‘love’ and ‘thought’ are formed with the weight value of 0 against the other constituent words, and thus the lyric feature information  40  of ‘sad, lonely’ is generated. Finally, with respect to the lyric feature information  40  of ‘heartening’, the constituent word of ‘hope’ is formed with the weight value of 0.8 against the other constituent words, the constituent word of ‘sea’ is formed with the weight value of 0.4 against the other constituent words, the constituent word of ‘love’ is formed with the weight value of 0.5 against the other constituent words, the constituent word of ‘thought’ is formed with the weight value of 0 against the other constituent words and thus the lyric feature information of ‘heartening’ is generated.  
      In addition, in the process of the step S 4 , the corresponding lyric feature information  40  is generated from each constituent word of the song by using the conversion table T shown in  FIG. 4 . More specifically, for example, in the case of using the conversion table T shown in  FIG. 4 , when any song includes only the constituent words ‘sea’, ‘thought’, and ‘hope’ among the constituent words in the conversion table T, the value of the lyric feature information  40  of ‘heart-warming’ for the song becomes 0.6 by adding the values 0.1, 0.1, and 0.4 which are the weight values of the constituent words ‘sea’, ‘thought’ and ‘hope’ in the lyric feature information of ‘heart-warming’, respectively. Similarly, the value of the lyric feature information  40  of ‘cheerful’ for the song becomes 1.0 by adding the values 0.1, 0.8, and 0.1 which are the weight values of the constituent words ‘sea’, ‘thought’ and ‘hope’ in the lyric feature information of ‘cheerful’, respectively. Similarly, with respect to each lyric feature information  40  listed in the conversion table T, each value of the song is determined by adding the weight values corresponding to each constituent word.  
      In parallel with the processes of the steps S 1 , S 2 , S 3 , and S 4 , only the sound feature information in each of the song feature information  20  corresponding to the entire songs is read from the song feature information database  3  and is outputted to the search process unit  8  (step S 5 ).  
      Based on these, in the search process unit  8 , for every song, the lyric feature information included in one entity of the search word feature information  30  (including the weight values of the lyric feature information  40 ) extracted at the step S 2  is compared with the entity of the lyric feature information  40  corresponding to each song converted at the step S 4 , and the sound feature information included in the search word feature information  30  is compared with the sound feature information corresponding to each song extracted at the step S 5 , and then the similarity between the lyric feature information  40  and sound feature information corresponding to each song and those corresponding to the inputted search word is calculated for every song (step S 6 ).  
      Further, based on the similarity calculated for each song, a reproduction list in which the songs to be outputted are arranged in higher order of the similarity is prepared (step S 7 ), and the songs arranged in the order equal to that of the reproduction list are extracted from the song database  2  and are outputted to the song output unit  10  (step S 8 ).  
      When one song is outputted, the user listening to the outputted song evaluates whether or not the outputted song is appropriate for the inputted search word at the step S 1  and inputs the evaluation result by using the input unit  9  (step S 9 ).  
      Further, when the outputted song is appropriate for the search word (step S 9 ; matching), the below-mentioned matching history information is updated (step S 11 ), and then the process proceeds to the step S 12 . On the other hand, when the outputted song is inappropriate for the search word at the evaluating step S 9  (step S 9 : non-matching), the below-mentioned non-matching history information is updated (step S 10 ), and then the process proceeds to the step S 12 .  
      Here, the non-matching history information updated at the above-mentioned step S 10  and the matching history information updated at the above-mentioned step S 11  will be explained with reference to  FIG. 5  in detail.  
      First, as the matching history information G, as shown in  FIG. 5A , in addition to the song feature information  20  of the song which is evaluated to be appropriate for the search word by the evaluation for the search word inputted by the user, based on the constituent word information included in the song feature information  20 , the lyric feature information  40  (the lyric feature information  40  corresponding to the song) generated by the method which is identical to the method illustrated at the step S 4  with reference to the effective conversion table T is included.  
      On the other hand, as the non-matching history information NG, as shown in  FIG. 5B , in addition to the song feature information  20  of the song which is evaluated to be inappropriate for the search word by the evaluation for the search word inputted by the user, based on the constituent word information included in the song feature information  20 , the lyric feature information  40  (the lyric feature information  40  corresponding to the song) generated by the method which is identical to the method illustrated at the above-mentioned step S 4  with reference to the effective conversion table T is included, in a similar manner to the case of the matching history information G.  
      Moreover, when the updating of the history information is finished with respect to the predetermined number of songs, based on the result, the content of the above-mentioned conversion table T and the content of the search word feature information  30  are updated (step S 12 ).  
      Next, whether the output of the final song in the reproduction list prepared at the above-mentioned step S 7  is finished is determined (step S 13 ). When the output of the final song is not finished (step S 13 : NO), the process returns to the above-mentioned step S 8 . At the step S 8 , the next song in the reproduction list is outputted and then the steps S 9  to S 12  are repeated with respect to the next song. On the other hand, in the determination of the step  13 , when the output of the final song is finished (step S 13 : YES), the song search process is completed.  
      Next, the update process of the conversion table T at the above-mentioned step S 12  will be explained with reference to FIGS.  6  to  8 .  
      In the update process of the conversion table T, as shown in  FIG. 6 , when the search word inputted at the timing for performing the update process is confirmed to have the same subjective feeling as the search word representing the subjective feeling represented by any entity of the song feature information  40  (step S 20 ) and when the subjective feeling is not matched (step S 20 : NO), the conversion table T is not updated and the process proceeds to the process for updating the next entity of the search word feature information  30 .  
      On the other hand, if the subjective feeling is matched (step S 20 : YES), then the process proceeds to the update process of the actual conversion table T.  
      In addition, in the below-mentioned update process, with respect to the predetermined number of the songs (forty songs (twenty appropriate songs and twenty inappropriate songs) in  FIGS. 7 and 8 ), the case of updating the conversion table T corresponding to the search word will be explained, based on the content of the constituent word included in the song which is evaluated to be appropriate for one search word (‘heart-warming’ in  FIGS. 7 and 8 ) and the content of the constituent word included in the song which is evaluated to be inappropriate for the search word. Also, in  FIGS. 7 and 8 , only the items needed for the update process of the conversion table T are extracted among the contents of the history information shown in  FIG. 5 .  
      In the actual update process, first, for every constituent word of the song which is evaluated to be appropriate for the matching history information (one storage address corresponding to one song, in  FIG. 7 ), all ‘0’s and ‘1’s in the vertical direction of  FIG. 7  are added for all the songs (twenty songs) and the added value is divided by the number of the songs (‘20’ in  FIG. 7 ) to obtain the average value AA (step S 21 ). For example, in the case of the constituent word of ‘love’ in the matching history information, since the number of the songs including the constituent word of ‘love’ is five, this number is divided by 20 which is the total number of songs. Thus, the average value AA for the constituent word of ‘love’ is determined to be 0.25. Further, the average calculating process is performed with respect to all the constituent words.  
      Next, similarly to the above, with respect to the non-matching history information, for every constituent word of the songs which are evaluated to be inappropriate, all ‘0’s and ‘1’s in the vertical direction of  FIG. 7  are added for all the songs and the added value is divided by the total number of the songs to obtain the average value DA (step S 21 ). For example, in the case of the constituent word of ‘love’ in the non-matching history information, since the number of the songs including the constituent word of ‘love’ is 14, the average value DA for the constituent word of ‘love’ is determined to be 0.70 by dividing the number of 14 with the total number of the songs. Further, the average calculating process is performed with respect to all the constituent words.  
      Here, the larger the difference between the average value AA and the average value DA for every constituent word, the higher the probability of representing the lyric feature information  40  corresponding to the current search word by the constituent word.  
      However, note that the average values AA and DA calculated by the above-mentioned process are not the result obtained by evaluating for the entire songs stored in the song database  2 . Accordingly, the confidence interval of each calculated average value (statistically, referred to as a sample ratio) must be obtained and the difference between the average value AA and the average value DA corresponding to each constituent word, (the absolute value of average value AA−average value DA), must be determined whether it can be used as the weight value of the history information of the constituent word. More specifically, assuming the confidence level of the confidence interval to be 90%, the difference is determined whether it can be used as the weight value of the history information of the constituent word by using the confidence interval calculated by the below-mentioned equation (1). That is, the confidence interval is calculated by the following equation for each constituent word: 
 
Confidence interval=2×1.65×[( AA ×(1− AA ))/ N]   1/2    (1), 
 
 where N is a number of songs. 
 
      Next, when the confidence interval is calculated, the absolute value of the value obtained by subtracting the average value DA from the average value AA is determined whether it is larger than the calculated confidence interval (step S 23 ).  
      Further, if the absolute value of the value obtained by subtracting the average value DA from the average value AA is larger than the calculated confidence interval (step S 23 : YES), the difference becomes a reliable value and is employed as the weight value of the corresponding lyric feature information (the lyric feature information of ‘heart-warming’ in  FIG. 7 ) in the conversion table T, and then is registered (stored) in the corresponding conversion table T (step S 24 ). On the other hand, in the step S 23 , if the absolute value of the value obtained by subjecting the average value DA from the average value AA is not larger than the calculated confidence interval (step S 23 : NO), the difference can not be used as a reliable value, and the weight value of the corresponding constituent word in the conversion table T is updated to ‘0’ (step S 25 ).  
      In addition, in the initial state of the song search apparatus S, since the history information includes the initial values set in advance and the number of songs which becomes the target of the history information is limited, as a result, new history information is stored by overwriting the old history information. Thereby, as the evaluation of the outputted songs is made, the subjective feeling of the user is reflected on the weight values of the conversion table T. This shows that the conversion table T can be updated accordingly in case the subjective feeling changes.  
      Next, when the evaluation for twenty songs (ten songs having the matching history information+(plus) ten songs having the non-matching history information) from the state in  FIG. 7  is made by the user, changes in the conversion table T will be illustrated with reference to  FIG. 8 . Also, since the updating method itself of the conversion table T after making the evaluation until the state shown in  FIG. 8  is completely identical to the case shown in  FIG. 7 , the detailed description thereof is omitted.  
      For example, for the constituent word ‘sea’ shown in  FIG. 8 , the songs including the constituent word of ‘sea’ (the value thereof being ‘1’) are stored preferentially in the matching history information, and thus the average value DA for the constituent word of ‘sea’ is reduced. Accordingly, it is appreciated that the constituent word of ‘sea’ contributes to the increment of the weight value of the lyric feature information of ‘heart-warming’.  
      Further, similarly, since the constituent word of ‘love’ is stored in the matching history information and the non-matching history information without any bias, the difference between the average value AA and the average value DA for the constituent word ‘love’ becomes smaller than the above-mentioned confidence interval, and thus the constituent word ‘love’ becomes the constituent word which is not related to the lyric feature information ‘heart-warming’.  
      As explained above, according to the operation of the song search apparatus S of the present embodiment, since songs are searched by comparing the entity of the search word feature information  30  corresponding to an inputted search word and the entity of the song feature information  20  corresponding to the stored songs, appropriate songs can be certainly searched by the inputted search word, and songs matched to the subjective feeling of a user can be much easily searched, compared with the case of searching songs using only an inputted search word.  
      Also, since at least the lyric feature information  40  corresponding to the subjective feeling identical to the subjective feeling represented by an inputted search word is generated, songs are searched by using the lyric feature information  40  reflecting the subjective feeling of a user, and thus songs suitable for the subjective feeling of the user can be easily searched.  
      Further, since the lyric feature information  40  is generated by using the conversion table T, the suitable lyric feature information  40  can be generated by an arrangement of a simple apparatus.  
      Moreover, since songs corresponding to an inputted search word are extracted by comparing the lyric feature information  40  which constitutes the search word feature information  30  corresponding to the inputted search word with the lyric feature information  40  corresponding to the song feature information  20  and simultaneously by comparing the sound feature information which constitutes the search word feature information  30  corresponding to the inputted search word with the sound feature information which constitutes the song feature information  20 , songs which are appropriate for the search word can be easily searched.  
      In addition, since the conversion table T is updated based on the evaluation of a user, the certainty of the conversion table T based on the evaluation of the user becomes higher, and thus songs according to the subjective feeling of the user can be easily searched.  
      Further, since each entity of the search word feature information  30  is updated based on the evaluation of a user, the certainty of the search word feature information  30  based on the evaluation of the user becomes higher, and thus songs according to the subjective feeling of the user can be easily searched.  
      Further, since the conversion table T or the search word feature information  30  is updated based on an inputted evaluation data by using the history information of each song, the conversion table T or the search word feature information  30  is updated according to the subjective feeling of a user by reflecting the past history thereof, and thus songs according to the subjective feeling of the user can be easily searched.  
      Also, since, for every constituent word, the weight value of the constituent word is updated by using the difference between the average value AA and the average value DA and also since the conversion table T is updated, the certainty of the conversion table T becomes higher, and thus songs according to the subjective feeling of a user can be easily searched.  
      In addition, although the case of applying the present invention to the song search apparatus S for accumulating and searching a plurality of songs in the above-mentioned embodiment was explained, the present invention may be applied to the image search apparatus which searches still images or moving images accumulated in accordance with the subjective feeling of a user.  
      Also, by recording a program corresponding to the flow chart shown in  FIGS. 3 and 6  in an information recording media such as a flexible disk, or by obtaining and recording the corresponding program by a network such as Internet, the program is read out and executed by using a general-purpose microcomputer etc. and thus the general-purpose microcomputer can be used as the search process unit  8  related to the embodiment.  
      The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.  
      The entire disclosure of Japanese Patent Application No. 2003-385714 filed on Nov. 14, 2003 and Japanese Patent Application No. 2004-327334 filed on Nov. 11, 2004 including the specification, claims, drawings and summary is incorporated herein by reference in its entirety.