Music selecting apparatus and method

BACKGROUND OF THE INVENTION

00011. Field of the Invention

0002This invention relates to a music selecting apparatus and method which selects one of a plurality of music pieces.

00032. Description of the Related Art

0004A well-known method to select a music piece preferred by a user of a plurality of music pieces involves extracting as data the physical characteristics of music pieces, classifying the plurality of music pieces in accordance with the extraction results, and using the result for music selection. As a method for obtaining physical characteristic data of each music piece, for example, a method for obtaining power spectrum data from music data is widely known (see Japanese Patent Application Kokai No. 10-134549). A method for obtaining physical characteristic data through the patterning of time-series changes using an N-gram method, based on the frequency bandwidth and the length of the reproduced sound of the music piece and the musical score, is also known.

0005However, in such conventional music selection methods, the physical characteristic data is not data which has a correlation with the sensitivities of the user. Hence there is the problem that the music piece imagined by the user is not necessarily selected.

SUMMARY OF THE INVENTION

0006It is an object of the present invention to provide a music selecting apparatus and method capable of providing a music piece appropriate to the sensitivities of the user.

0007A music selecting apparatus according to the present invention is an apparatus for selecting a music piece from a plurality of music pieces in accordance with an input operation, comprising: a first storage device which stores, as data, a degree of chord change for each of the plurality of music pieces; a setting device which sets a sensitivity word for music selection in accordance with the input operation; and, a music selector which detects a music piece having a degree of chord change corresponding to the sensitivity word set by the setting device, in accordance with the chord change degree for each of the plurality of music pieces.

0008A music selecting method according to the present invention is a method for selecting a music piece from among a plurality of music pieces in accordance with an input operation, comprising the steps of: storing, as data, a degree of chord change for each of the plurality of music pieces; setting a sensitivity word for music selection in accordance with the input operation; and, detecting a music piece having a degree of chord change corresponding to the set sensitivity word, in accordance with the chord change degree for each of the plurality of music pieces.

0009A music selecting apparatus according to the present invention is an apparatus for selecting a music piece from among a plurality of music pieces in accordance with an input operation, comprising: a first storage device which stores, as data, a characteristic value of at least one characteristic parameter for each of the plurality of music pieces; a setting device which sets a sensitivity word for music selection from among a plurality of sensitivity words, in accordance with the input operation; a second storage device which stores, as data, a correction value for each of the plurality of sensitivity words; a reading portion which reads, from the second storage device, the correction value corresponding to the sensitivity word for the music selection set by the setting device; a correction device which corrects the characteristic value of characteristic parameter for each of the plurality of music pieces in accordance with correction value read by the reading portion to compute a sensitivity matching degree; a music selector which selects at least one music piece from among the plurality of music pieces, in accordance with the sensitivity matching degree for each of the plurality of music pieces, computed by the correction device; a matching judgment device which judges whether the at least one music piece selected by the music selector matches the sensitivity word for the music selection, in accordance with an input operation; a learning value storage device which computes a learning value in accordance with a result of the judgment by the matching judgment device, and stores the computed learning value in association with the sensitivity word for the music selection; and, a learning judgment device which judges, when the sensitivity word for the music selection is set by the setting device, whether the learning value corresponding to the sensitivity word for the music selection exist in the learning value storage device; and wherein when the learning value corresponding to the sensitivity word for the music selection is judged by the learning judgment device to be stored in the learning value storage device, the correction device corrects the characteristic value of characteristic parameter for each of the plurality of music pieces in accordance with the stored learning value to compute the sensitivity matching degree.

0010A music selecting method according to the present invention is a method for selecting a music piece from among a plurality of music pieces in accordance with an input operation, comprising the steps of: storing a characteristic value of at least one characteristic parameter as data for each of the plurality of music pieces; setting a sensitivity word for music selection from among a plurality of sensitivity words in accordance with the input operation; storing a correction value as data for each of the plurality of sensitivity words in a second storage device; reading the correction value corresponding to the sensitivity word for the music selection from the second storage device; correcting characteristic value of characteristic parameters for each of the plurality of music pieces in accordance with the read correction value to compute a sensitivity matching degree; selecting at least one music from among the plurality of music pieces in accordance with the sensitivity matching degrees computed for each of the plurality of music pieces; judging whether the selected music piece matches the sensitivity word for the music selection, in accordance with the input operation; computing a learning value in accordance with the judgment result, and storing the computed learning value in a learning value storage device in association with the sensitivity word for the music selection; judging whether the learning value corresponding to the sensitivity word for the music selection exists in the learning value storage device at the time the sensitivity word for the music selection is set; and, when it is judged that the learning value corresponding to the sensitivity word for the music selection is stored in the learning value storage device, correcting the characteristic value of characteristic parameter for each of the plurality of music pieces in accordance with the stored learning value to compute the sensitivity matching degree.

BRIEF DESCRIPTION OF THE DRAWINGS

0011<figref idref="DRAWINGS">FIG. 1</figref> is a block diagram showing the configuration of a music selecting apparatus according to the present invention;

0012<figref idref="DRAWINGS">FIG. 2</figref> shows a default database;

0013<figref idref="DRAWINGS">FIG. 3</figref> is a flowchart showing music selection operation;

0014<figref idref="DRAWINGS">FIG. 4</figref> is a flowchart showing the continuous portion of the music selection operation of <figref idref="DRAWINGS">FIG. 3</figref>;

0015<figref idref="DRAWINGS">FIG. 5</figref> is a flowchart showing a learning routine;

0016<figref idref="DRAWINGS">FIG. 6</figref> is a flowchart showing personal learning value computation operation;

0017<figref idref="DRAWINGS">FIG. 7</figref> is a flowchart showing another example of the learning routine;

0018<figref idref="DRAWINGS">FIG. 8</figref> is a flowchart showing personal learning value computation operation in the learning routine of <figref idref="DRAWINGS">FIG. 7</figref>;

0019<figref idref="DRAWINGS">FIG. 9</figref> shows a second personal learning value database having unmatched music data; and,

0020<figref idref="DRAWINGS">FIG. 10</figref> is a flowchart showing a portion of music selection operation to which the learning routine of <figref idref="DRAWINGS">FIG. 7</figref> is applied.

DETAILED DESCRIPTION OF THE INVENTION

0021Below, embodiments of the invention are explained in detail, referring to the drawings.

0022<figref idref="DRAWINGS">FIG. 1</figref> shows a music selecting apparatus according to the present invention. The music selecting apparatus comprises a music input device <b>1</b>, input operation device <b>2</b>, data storing devices <b>3</b>, <b>4</b> and <b>5</b>, control device <b>6</b>, display device <b>7</b>, music reproducing device <b>8</b>, digital-analog converter <b>9</b>, and speaker <b>10</b>.

0023The music input device <b>1</b> is connected to the control device <b>6</b> and data storing device <b>3</b>, and is a device for input of audio signals (for example, PCM data) of digitized music pieces to the music selecting apparatus. As the music input device <b>1</b>, for example, a disc player which plays a disc such as CD, or a streaming interface which receives streaming music data, is employed. The input operation device <b>2</b> is a device operated by the user of the music selecting apparatus to input data and instructions. In addition to character keys and numeric keys, the input operation device <b>2</b> is provided with a “YES” key, a “NO” key, an “END” key, a “NEXT MUSIC” key, and other specialized keys. The output of the input operation device <b>2</b> is connected to the control device <b>6</b>. The types of keys of the input operation device <b>2</b> are not necessarily limited to those described above.

0024The data storing device <b>3</b>, which is the third storage means, stores, as files, music data supplied from the music input device <b>1</b>. Music data is data indicating the reproduced sounds of a music piece, and may be, for example, PCM data, MP3 data, MIDI data, or similar. The music name, singer name, and other music information is stored for each music piece in the data storing device <b>3</b>. Music data accumulated in the data storing device <b>3</b> corresponds to a plurality of music pieces <b>1</b> through n (where n is greater than one). The data storing device <b>4</b> stores as a characteristic parameter database (first storage device), for each of the n music pieces for which music data is accumulated in the data storing device <b>3</b>, characteristic values for the degree of chord change (<b>1</b>), degree of chord change (<b>2</b>), degree of chord change (<b>3</b>), beat (number of beats per unit time), maximum beat level, mean amplitude level, maximum amplitude level, and the key, as characteristic parameters. The degree of chord change (<b>1</b>) is the number of chords per minute in the music piece; the degree of chord change (<b>2</b>) is the number of types of chords used in the music piece; and the degree of chord change (<b>3</b>) is the number of change points, such as discord, which change an impression of the music piece during the chord progression.

0025Chords themselves have elements which may provide depth to a music piece, or impart a sense of tension to the listener, or similar. Further, a music piece may be provided with atmosphere through a chord progression. Chords having such psychological elements are optimal as music-characterizing quantities used by a music selecting apparatus to select music pieces through sensitivity words, and in addition to the simple characteristics of the melody, it is thought that the intentions of the composer, including the contents of the lyrics, may to some extent be reflected therein; hence chords are employed as a portion of the characteristic parameters.

0026In the data storing device <b>4</b>, for each sensitivity word previously determined are stored, as the default database (second storage device), an average value and an unbiased variances for characteristic parameters, comprising the degree of chord change (<b>1</b>), degree of chord change (<b>2</b>), degree of chord change (<b>3</b>), beat, maximum beat level, mean amplitude level, maximum amplitude level, and the key. The average value and unbiased variance represent a characteristic value for each of the characteristic parameters, as well as a correction value used for computation of a sensitivity matching degree. The average value and unbiased variance are described below. <figref idref="DRAWINGS">FIG. 2</figref> shows, in a table, the average values and unbiased variances of each of the characteristic parameters for different sensitivity words, which are the contents of the default database. In <figref idref="DRAWINGS">FIG. 2</figref>, Ma<b>1</b> to Ma<b>6</b>, Mb<b>1</b> to Mb<b>6</b>, and similar are average values, and Sa<b>1</b> to Sa<b>6</b>, Sb<b>1</b> to Sb<b>6</b>, and similar are unbiased variances.

0027Here, the sensitivity word is a word expressing feelings felt when a listener listens to a music piece. Examples are “rhythmical”, “gentle”, “bright”, “sad” “healing”, and “lonely”.

0028A matched music database (fourth storage device) and unmatched music database (sixth storage device) are formed in the data storing device <b>5</b>. In each of these databases is stored data for 50 music pieces for each sensitivity word. When music data for more than 50 music pieces is to be written, the new data is written while erasing the oldest data. Of course the number of music pieces stored for each sensitivity word in the matched music database and in the unmatched music database is not limited to 50 music pieces, but may be a different number of music pieces.

0029The control device <b>6</b> comprises for example a microcomputer, and performs music selection operation in accordance with an input operation by a user, described below.

0030The display device <b>7</b> displays selection fields related to the control of the control device <b>6</b>, the contents input to the music input device <b>1</b>, and a list of music pieces presented to the user.

0031The music reproducing device <b>8</b> reads music data for a music piece selected by the user from the data storing device <b>3</b>, and reproduces a digital audio signal in accordance with the read music data. The digital-analog converter <b>9</b> converts the digital audio signals reproduced by the music reproducing device <b>8</b> into analog audio signals, which are supplied to the speaker <b>10</b>.

0032Next, music selection operation in a music selection system of this configuration is explained. It is assumed that a single user uses the music selecting apparatus; in the case of a device used by a plurality of users, when starting the music selection operation, a user ID identifying the user must be input via the input operation device <b>2</b>. This is in order to specify the user utilizing personal learning values, described below.

0033When music selection operation begins, the control device <b>6</b> first causes the display device <b>7</b> to display an image in order to request selection of a sensitivity word, as shown in <figref idref="DRAWINGS">FIG. 3</figref> and <figref idref="DRAWINGS">FIG. 4</figref> (step S<b>1</b>). As sensitivity words for music selection, “rhythmical”, “gentle”, “bright”, “sad”, “healing”, “lonely”, and other items are displayed on the screen of the display device <b>7</b>, and in addition an “other sensitivity word” items is displayed. At the same time, an instruction to select from among these displayed items is shown. The user can perform an input operation through the input operation device <b>2</b> to select one of these sensitivity words or another sensitivity word in response to the display. After executing step S<b>1</b>, the control device <b>6</b> judges whether there has been operation input (step S<b>2</b>). If there has been operation input, the control device <b>6</b> judges whether one of the sensitivity words displayed has been selected, in accordance with the output from the input operation device <b>2</b> (step S<b>3</b>). That is, a judgment is made as to whether one sensitivity word of the sensitivity words displayed, or “other sensitivity word”, has been selected.

0034If one of the displayed sensitivity words has been selected, the control device <b>6</b> captures the selected sensitivity word (step S<b>4</b>), and judges whether, for the selected sensitivity word, there exist personal learning values (step S<b>5</b>). The personal learning values are the average value and unbiased variance, specific to the user, of each of the characteristic parameters for the selected sensitivity word; the average values and unbiased variances are computed in a step described below, and stored in a personal-learning value database (fifth storage device) in the data storing device <b>4</b>. If personal learning values for the selected sensitivity word do not exist in the data storing device <b>4</b>, an average value and an unbiased variance for each of the characteristic parameters corresponding to the selected sensitivity word are read from the default database (step S<b>6</b>). On the other hand, if personal learning values for the selected sensitivity word exist in the data storing device <b>5</b>, an image asking the user whether to select a music piece using the personal learning values is displayed on the display device <b>7</b> (step S<b>7</b>). The user can perform an input operation on a “YES” key or a “NO” key using the input operation device <b>2</b>, based on the display, to select whether or not to use personal learning values. After execution of step S<b>7</b>, the control device <b>6</b> judges whether there has been input operation of the “YES” key or of the “NO” key (step S<b>8</b>). If there is input operation of the “YES” key indicating that personal learning values are to be used, the average value and unbiased variance of each of the characteristic parameters corresponding to the selected sensitivity word are read from the personal learning value database (step S<b>9</b>). If there is input operation of the “NO” key indicating that personal learning values are not to be used, processing proceeds to step S<b>6</b>, and the average value and unbiased variance of each of the characteristic parameters corresponding to the selected sensitivity word are read from the default database.

0035Upon reading the average values and unbiased variances of each of the characteristic parameters in step S<b>6</b> or in step S<b>9</b>, the control device <b>6</b> computes a sensitivity matching degree for each of the n music pieces (step S<b>10</b>). The sensitivity matching degree for the i-th music piece is computed as follows. <br />Sensitivity matching degree=(1/|a(i)−Ma|)×(1/Sa)+(1/|b(i)−Mb|)×(1/Sb)+(1/|c(i)−Mc|)×(1/Sc)+(1/|d(i)×Md|)×(1/Sd)+(1/|e(i)−Me|)×(1/Se)+(1/|f(i)−Mf|)×(1/Sf)+(1/|g(i)−Mg|)×(1/Sg)+(1/|h(i)−Mh|)×(1/Sh)

0036In this formula, the degree of chord change (<b>1</b>) of the i-th music piece is a(i), the degree of chord change (<b>2</b>) of the i-th music piece is b(i), the degree of chord change (<b>3</b>) of the i-th music piece is c(i), the beat of the i-th music piece is d(i), the maximum beat level of the i-th music piece is e(i), the mean amplitude level of the i-th music piece is f(i), the maximum amplitude level of the i-th music piece is g(i), and the key of the i-th music piece is h(i). Assume that the selected sensitivity word is A, and the average values and unbiased variances for this sensitivity word A are Ma, Sa for the degree of chord change (<b>1</b>), Mb, Sb for the degree of chord change (<b>2</b>), Mc, Sc for the degree of chord change (<b>3</b>), Md, Sd for the beat, Me, Se for the maximum beat level, Mf, Sf for the mean amplitude level, Mg, Sg for the maximum amplitude level, and Mh, Sh for the key.

0037Further, when computing the sensitivity matching degree, the units of numerical values differ depending on the characteristic parameter, and so levels may be adjusted. In the formula to compute the sensitivity matching degree, for example, the degree of chord change (<b>1</b>) may be computed as (100/|a(i)−Ma|)×(1/Sa), increasing the value by a factor of 100.Other degrees of chord change and the beat may similarly be increased by a factor of 100.

0038Upon computing the sensitivity matching degree for each of n music pieces, the control device <b>6</b> makes up a music list showing music pieces in order of the greatest sensitivity matching degree (step S<b>11</b>), and causes the display device <b>7</b> to display an image showing this music list (step S<b>12</b>). The screen of the display device <b>7</b> shows music names, singer names, and other music information, read from the data storing device <b>3</b>, and displayed with music pieces in the order of greatest sensitivity matching degree.

0039There are cases in which, in step S<b>3</b>, “other sensitivity word” is selected; that is, the user desires a music piece which conforms to a sensitivity word other than the sensitivity words prepared in advance. In such a case, the control device <b>6</b> causes the display device <b>7</b> to display an image to request input of a sensitivity word (step S<b>13</b>). The user can use the input operation device <b>2</b> to input, as text, any arbitrary sensitivity word, in accordance with the displayed instructions. After execution of step S<b>13</b>, the control device <b>6</b> judges whether text has been input (step S<b>14</b>). If there has been input, the control device <b>6</b> captures and stores the input text as a sensitivity word (step S<b>15</b>). The control device <b>6</b> uses the music pieces <b>1</b> through n for which music data is accumulated in the data storing device <b>3</b> to make up a random music list (step S<b>16</b>), and then proceeds to the above step S<b>12</b> and causes the display device <b>7</b> to display an image showing this music list. On the screen of the display device <b>7</b> are listed, in random order, the names, singers, and other music information for the music pieces.

0040The sensitivity word captured at step S<b>15</b> can be included in the sensitivity words displayed at step S<b>1</b> of the next music selection operation.

0041After execution of step S<b>12</b>, the variable m is set to 1 (step S<b>17</b>), music data for the m-th music piece in the music list is read from the data storing device <b>3</b> and is supplied to the music reproducing device <b>8</b>, to specify music reproduction (step S<b>18</b>). The music reproducing device <b>8</b> reproduces a digital signal on the music data for the m-th music piece thus supplied, and the digital signal is supplied to the digital-analog converter <b>9</b>. After conversion into analog audio signals in the digital-analog converter <b>9</b>, reproduced sounds for the m-th music piece are output from the speaker <b>10</b>. Thus, the user can listen to the reproduced sounds of the music piece.

0042An image is displayed on the display device <b>7</b> to ask the user whether or not to perform personal learning for the music piece being reproduced (step S<b>19</b>). The user can use the input operation device <b>2</b> to operate the “YES” key or the “NO” key, in accordance with the displayed contents, to select whether or not to perform personal learning for the music piece being reproduced. After execution of step S<b>19</b>, the control device <b>6</b> judges whether there has been operation input of the “YES” key or of the “NO” key (step S<b>20</b>). If there has been input due to operation of the “YES” key, indicating that personal learning is to be performed, processing proceeds to the learning routine.

0043If there has been input of the “NO” key indicating that personal learning is not to be performed, the display device <b>7</b> is caused to display an image asking the user whether to proceed to reproduction of the next music piece on the list of music pieces, or whether to halt music selection (step S<b>21</b>). By operating the input operation device <b>2</b> in accordance with the displayed contents, the user can begin reproduction of the next music piece on the displayed music list after the music piece currently being reproduced, or can halt music selection without selecting another music piece. After execution of step S<b>21</b>, the control device <b>6</b> judges whether there has been input operation of the “NEXT MUSIC” key (step S<b>22</b>). If there has not been input operation of the “Next music” key, the control device judges whether there has been operation of the “END” key (step S<b>23</b>).

0044If there has been input of the “NEXT MUSIC” key, the variable m is increased by <b>1</b> to compute the new value of the variable m (step S<b>24</b>), and a judgment is made as to whether the variable m is greater than the final number MAX of the music list (step S<b>25</b>). If m>MAX, the music selection operation ends. On the occasion of this ending, the display device <b>7</b> may be caused to display an image informing the user that music pieces have been reproduced up to the final number of the music list. On the other hand, if m<MAX, processing returns to step S<b>18</b> and the above operations are repeated.

0045If there has been input of the “END” key, the music reproducing device <b>8</b> is instructed to halt music reproduction (step S<b>26</b>). By this means music selection by the control device <b>6</b> ends; but processing may also return to step S<b>1</b>.

0046When execution of the above learning routine has been begun, the control device <b>6</b> first causes the display device <b>7</b> to display an image to ask the user whether the music piece currently being reproduced is a music piece which matches the sensitivity word which has been selected or input, as shown in <figref idref="DRAWINGS">FIG. 5</figref> (step S<b>31</b>). The user can use the input operation device <b>2</b> to input “YES” or “NO”, in accordance with the displayed contents, to select whether or not the music piece being reproduced matches the sensitivity word. After execution of step S<b>26</b>, the control device <b>6</b> judges whether there has been input using either the “YES” key or the “NO” key (step S<b>32</b>). If there is input using the “YES” key, indicating that the music piece being reproduced matches the sensitivity word, matched music data indicating this music piece is written to the matched music database of the data storing device <b>5</b> (step S<b>33</b>). On the other hand, if there is input using the “NO” key, indicating that the music piece being reproduced does not match the sensitivity word, the learning routine is ended and processing returns to the above step S<b>21</b>.

0047After execution of step S<b>33</b>, the control device <b>6</b> judges whether there is a sensitivity word for which the number of matched music pieces written as matched music data to the matched music database has reached 10 music pieces (a predetermined number of music pieces) (step S<b>34</b>). If it is judged that there is a sensitivity word for which the number of matched music pieces is 10 music pieces or greater, matched music data is read from the matched music database of the data storing device <b>5</b>, unmatched music data is read from a unmatched music database (step S<b>35</b>), and the read data is used to compute personal learning values using statistical processing (step S<b>36</b>). In step S<b>34</b>, the predetermined number of music pieces is stipulated to be 10 music pieces, but another value for the number of music pieces may be used.

0048Computation of personal learning values is explained for a sensitivity word A, for which the number of matched music pieces has reached 10 or greater. As shown in <figref idref="DRAWINGS">FIG. 6</figref>, a characteristic value for each of the characteristic parameters (degree of chord change (<b>1</b>), degree of chord change (<b>2</b>), degree of chord change (<b>3</b>), beat (number of beats per unit time), maximum beat level, mean amplitude level, maximum amplitude level, and key) for each music piece indicated by the matched music data corresponding to the sensitivity word A in the matched music database is read from the characteristic parameter database of the data storing device <b>4</b> (step S<b>51</b>), and the average value Mave of the read characteristic values for each characteristic parameter are computed (step S<b>52</b>). Further, the unbiased variance S for each characteristic parameter is also computed (step S<b>53</b>). When computing the unbiased variance S of one characteristic parameter of the sensitivity word A, if the music pieces indicated by the matched music data corresponding to the sensitivity word A are M<b>1</b> to Mj (where for example 50≧j≧10), and the characteristic values of one characteristic parameter for the respective music pieces M<b>1</b> to Mj are C<b>1</b> to Cj, then the average value Mave of the characteristic values C<b>1</b> to Cj for one characteristic parameter can be expressed by <br />Mave=C1+C2+ . . . +Cj/j

0049The unbiased variance S of a characteristic parameter of the sensitivity word A can be expressed by <br />S={(Mave−C1)²+(Mave−C2)²+ . . . +(Mave−Cj)²}/ (j−1)

0050The control device <b>6</b> writes the average value Mave and unbiased variance S computed for each characteristic parameter into fields for the respective characteristic parameters corresponding to the sensitivity word A in the personal learning value database (step S<b>54</b>).

0051After thus computing personal learning values, the control device <b>6</b> returns to the above step S<b>21</b>, and continues operation as described above.

0052Through this music selection operation, a music list conforming to a selected sensitivity word can be presented to the user. Further, in music selection using personal learning values, as a user utilizes this music selection system, it becomes possible to provide music pieces which more closely conform to the sensitivities of the user.

0053In the above embodiment, the degree of chord change (<b>1</b>), degree of chord change (<b>2</b>), degree of chord change (<b>3</b>), beat (number of beats per unit time), maximum beat level, mean amplitude level, maximum amplitude level, and the key are described as characteristic parameters, but others are possible. Also, the sensitivity matching degree may be computed for at only at least one of the three degrees of chord change (<b>1</b>) through (<b>3</b>).

0054Further, degrees of chord change are not limited to the above-described number of chords per minute in the music piece, number of types of chords used in the music piece, and number of change points, such as discord, which impart an impression of the music piece during the chord progression. For example, the amount of change in the chord root, or a change from a major chord to a minor chord, or the number of changes to other types of chords, can also be used as degrees of chord change.

0055In the above-described embodiment, average values and unbiased variances are used as correction values, but other values may be used. In place of unbiased variances, for example, a multiplicative factor, variance or other weighting value to correct a degree of chord change or other characteristic value may be used. When using a variance in place of an unbiased variance, the variance of one characteristic parameter for sensitivity word A as described above can be expressed by the following equation. The unmatched music data for the music piece is written to the unmatched music database of the data storing device <b>5</b> (step S<b>34</b>). <br />Variance={(Mave−C1)²+(Mave−C2)²+ . . . +(Mave−Cj)²}/j

0056<figref idref="DRAWINGS">FIG. 7</figref> shows another example of a learning routine in the above step S<b>30</b>. In this learning routine, if there is input operation of the “YES” key indicating a match of the music piece being reproduced in step S<b>32</b> with a sensitivity word, the control device <b>6</b> writes matched music data indicating the music piece to the matched music database of the data storing device <b>5</b> (step S<b>33</b>); on the other hand, if there is input operation of the “NO” key indicating that the music piece being reproduced does not match the sensitivity word, unmatched music data indicating the music piece is written to the unmatched music database (sixth storage device) of the data storing device <b>5</b> (step S<b>37</b>), the learning routine is ended, and processing proceeds to the above step S<b>21</b>.

0057After execution of step S<b>33</b>, the control device <b>6</b> judges whether the number of matched music pieces written as matched music data to the matched music database has reached <b>10</b> music pieces (a predetermined number of music pieces) (step S<b>38</b>). If the number of matched music pieces is judged to be 10 or greater, matched music data is read from the matched music database of the data storing device <b>5</b>, unmatched music data is read from the unmatched music database (step S<b>39</b>), and the read data is used to compute personal learning values through statistical processing (step S<b>40</b>). In step S<b>38</b>, the predetermined number of music pieces is stipulated to be 10 music pieces, but of course a different value for the number of music pieces may be used.

0058In the personal learning value computation of step S<b>40</b>, as shown in <figref idref="DRAWINGS">FIG. 8</figref>, an average value Mave and an unbiased variance S of a characteristic value for each characteristic parameter are computed for a sensitivity word A using the matched music data, and these values are written to the fields for the respective characteristic parameters corresponding to the sensitivity word A in the personal learning value database (steps S<b>51</b> to S<b>54</b>). Thereafter, a characteristic value for each of the characteristic parameters for each music piece indicated by unmatched music data for the sensitivity word A in the unmatched music database is read from the characteristic parameter database of the data storing device <b>4</b> (step S<b>55</b>), and the average value Mave′ of characteristic values is computed for each characteristic parameter using the unmatched music data (step S<b>56</b>). Also, the unbiased variance S′ is computed for each characteristic parameter using the unmatched music data (step S<b>57</b>). The methods for computing the average value Mave′ and unbiased variance S′ are similar to those used for the average value Mave and unbiased variance S.

0059The control device <b>6</b> writes the average value Mave′ and unbiased variance S′ computed for each characteristic parameter to the respective characteristic parameter fields corresponding to the sensitivity work A in the personal learning value database (step S<b>58</b>). The personal learning values computed based on this unmatched music data are stored in a second personal learning value database (seventh storage device) as shown in <figref idref="DRAWINGS">FIG. 9</figref>. In <figref idref="DRAWINGS">FIG. 9</figref>, M′a<b>1</b> to M′a<b>6</b>, M′b<b>1</b> to M′b<b>6</b>, and so on are average values, and S′a<b>1</b> to S′a<b>6</b>, S′b<b>1</b> to S′b<b>6</b>, and so on are unbiased variances. Only the average values Mave′ may be used as personal learning values for unmatched music data.

0060When providing personal learning values for unmatched music data, when in music selection operation there is input operation of the “YES” key in step S<b>8</b> indicating that personal learning values are to be used, as shown in <figref idref="DRAWINGS">FIG. 10</figref>, average values and unbiased variances are read from the personal learning value database for matched music data and for unmatched music data for each of the characteristic parameters corresponding to the selected sensitivity word (step S<b>61</b>), and in addition, an unmatched correction value is computed in accordance with at least one of the average value and unbiased variance for the unmatched music data (step S<b>62</b>). The unmatched correction value is computed by, for example, multiplying the average value by a coefficient, or by multiplying the reciprocal of the unbiased variance by a coefficient. The coefficient is specified for each of the characteristic parameters.

0061After execution of step S<b>62</b>, the control device <b>6</b> computes a sensitivity matching degree for each of n music pieces (step S<b>63</b>). The sensitivity matching degree is computed using the following equation. In this equation, αa, αb, αc, αd, αe, αf, αg, αh are unmatched correction values, computed in step S<b>62</b>, for the characteristic parameters, which are the degree of chord change (<b>1</b>), degree of chord change (<b>2</b>), degree of chord change (<b>3</b>), beat (number of beats per unit time), maximum beat level, mean amplitude level, maximum amplitude level, and the key, respectively. <br />Sensitivity matching degree={(1/|a(i)−Ma|)×(1/Sa)−αa}+{(1/|b(i)−Mb|)×(1/Sb)−αb}+{(1/|c(i)−Mc|)×(1/Sc)−αc}+{(1/|d(i)−Md|)×(1/Sd)−αd}+{(1/|e(i)−Me|)×(1/Se)−αe}+{(1/|f(i)−Mf|)×(1/Sf)−αf}+{(1/|g(i)−Mg|)×(1/Sg)−αg}+{(1/|h(i)−Mh|)×(1/Sh)−αh}

0062The unmatched correction values αa, αb, αc, αd, αe, αf, αg, αh act so as to reduce the sensitivity matching degree computed using matched music data based on personal learning values.

0063In step S<b>63</b>, after computation of sensitivity matching degrees, processing proceeds to step S<b>11</b> and a music list is made up, similarly to the music selection operation of <figref idref="DRAWINGS">FIG. 3</figref>.

0064The method for computing the sensitivity matching degree is not limited to the above example. For example, the following equation may also be used in computation. Here σ is the standard deviation computed from characteristic values of matched music data. <br />Sensitivity matching degree={(1/a(i)−Ma)²)×(σ/Sa)−αa}+{(1/b(i)−M )²)×(σ/Sb)−αb}+{(1/c(i)−Mc)²)×(σ/Sc)−αc}+{(1/d(i)−Md)²)×(σ/Sd)−αd}+{(1/e(i)−Me)²)×(σ/Se)−αe}+{(1/f(i)−Mf)²)×(σ/Sf)−αf}+{(1/g(i)−Mg)²)×(σ/Sg)−αg}+{(σ/h(i)−Mh)²)×(σ/Sh)−αh}

0065In the above embodiment, “rhythmical”, “gentle”, “bright”, “sad” “healing”, and “lonely” are selected sensitivity words, but other sensitivity words may be used. For example, “joyful” or other sensitivity words may of course be used.

0066Thus, according to the present invention, music pieces matching with the sensitivities of the user can be presented to the user, so that music selection by the user becomes easy.

0067Also, according to the present invention, the sensitivities of the user relating to music selection are learned, so that music pieces more closely matching with those sensitivities can be provided to the user, and music selection by the user is made easy.

0068This application is based on a Japanese Application No. 2003-350728 and No. 2004-095916 which are hereby incorporated by reference.