JP5521554B2 - Text conversion device, method, and program - Google Patents

Description

(Description of related applications)
This application claims the priority of the previous Japanese Patent Application No. 2008-037603 (filed on Feb. 19, 2008), and the entire description of the previous application is incorporated herein by reference. Is considered to be.
The present invention relates to a text conversion device, a text conversion method, a text conversion program, a speech synthesizer, and a robot, and in particular, a text conversion device, a text conversion method, a text conversion program, and a voice that perform conversion that facilitates transmission of text contents. The present invention relates to a synthesis apparatus and a robot.

  Patent Document 1 discloses a sentence conversion technique for converting a character string described in a certain natural language into a character string in another representation of the natural language using a conversion rule prepared for each conversion purpose. Yes.

  Patent Document 2 includes a driving load determination unit that determines a driving load of a driver who is driving a vehicle, controls the driver's voice output unit according to the driving load of the driver, and sets a reading pause period and speech rate. Techniques for changing are disclosed.

  Patent Document 3 discloses a technique for controlling the sound quality of speech synthesis according to user attribute information in a voice response service device.

  Patent Document 4 discloses a technique for estimating a speaker's emotion based on feature amounts such as sound pressure, pitch frequency, and duration of input speech.

Japanese Patent No. 3932350 JP-A-2005-070703 Japanese Patent No. 3936351 JP 2003-228391 A

The entire disclosures of Patent Documents 1 to 4 above are incorporated herein by reference. The following is an analysis of the related art according to the present invention.
The listener does not always use his / her full ability to listen to the content, and may be missed or misunderstood depending on the sequential psychological situation. An object of the present invention is to provide a text conversion device, a text conversion method, a text conversion program, a speech synthesizer, and a robot that perform text conversion so that the semantic content of the listener is easily transmitted in consideration of the psychological situation of the listener. There is.

  In this regard, Patent Document 1 includes, as a specific application example, an application example to (A) question answering system, (B) sentence compression system, (C) recommendation system, (D) difficult sentence conversion system, and Although there are examples of conversion to different expressions that will be performed in the past, there is no guarantee that the text after these conversions will be easily communicated to the listener. In addition, Patent Document 1 suggests application to conversion / inverse conversion between written words and spoken words (paragraph 0064). However, the purpose of conversion is to generate text that is easy to convey to the listener, and a specific example for that purpose. No specific conversion rules have been disclosed.

  In addition, the “driver's driving load” as referred to in Patent Document 2 specifically refers to the vehicle speed. When driving, the reading speed is higher than normal (the reading speed for other passengers). It is only disclosed that audio output is performed.

  Further, although the technique described in Patent Document 3 does not perform the text conversion as originally mentioned as the above object, it is impossible to cope with the psychological situation of the listener that changes every moment.

  Further, Patent Document 4 describes a technique for estimating a speaker's emotion from input speech. Specifically, the application to a nursing robot that performs an inquiry and measures a change in emotion from its feature amount is disclosed. It has only been done.

According to a first aspect of the present invention , by inputting a parameter representing a user's psychological state and text, and replacing a word in the text using a word pair whose meaning does not change even if replaced, Score when a plurality of text conversion candidates are created within a range that does not change the meaning of the input text, and the text is converted using the word pairs set for each word pair for each text conversion candidate Provided is a text conversion device that performs a conversion operation of input text by obtaining a score indicating the ease of understanding when the output text is received as speech using, and selecting a text conversion candidate having a score that matches the input parameter. .

According to a second aspect of the present invention, there is provided a text conversion method by a text conversion device , a step of inputting a parameter representing a user's psychological state and text, and a word pair whose meaning does not change even if replaced. Is used to generate a plurality of text conversion candidates from the text by replacing words in the text, and for each text conversion candidate, convert the text using the word pairs set for each word pair A score indicating the ease of understanding when the output text is received as speech using each score, and selecting a text conversion candidate having a score commensurate with the input parameter. , converting said inputted text in a range that does not alter the containing text conversion method is Hisage It is.

According to a third aspect of the present invention, there is provided a text conversion program for realizing the function of the text conversion device . This text conversion program can be recorded on a computer-readable storage medium.

  According to the present invention, it is possible to convert an arbitrary text into a text whose semantic content is easily transmitted to the listener. The reason is that a configuration is adopted in which text conversion is performed with parameters representing the psychological situation of the listener as input. Also, derived from this effect, for example, the burden of considering the listener's situation when creating a text to be read is reduced, and the creation of these texts is facilitated.

It is a figure for explaining the outline of the present invention. It is a block diagram showing the structure of the text converter which concerns on the 1st Embodiment of this invention. It is a figure for demonstrating the relationship between the pitch frequency of an audio | voice, and the urgency level of a user. It is a block diagram showing the detailed structure of the text conversion part of the text converter which concerns on the 1st Embodiment of this invention. It is a figure for demonstrating the structure of the word conversion database of the text converter which concerns on the 1st Embodiment of this invention. It is a figure for demonstrating operation | movement of the text conversion apparatus which concerns on the 1st Embodiment of this invention. It is a block diagram showing the structure of the text conversion apparatus which concerns on the 2nd Embodiment of this invention. It is a block diagram showing the detailed structure of the text conversion part of the text converter which concerns on the 2nd Embodiment of this invention. It is a figure for demonstrating operation | movement of the text conversion apparatus which concerns on the 2nd Embodiment of this invention. It is a block diagram showing the structure of the text conversion apparatus which concerns on the 3rd Embodiment of this invention. It is a block diagram showing the detailed structure of the text conversion part of the text converter which concerns on the 3rd Embodiment of this invention.

11 Microphone (voice input unit)
DESCRIPTION OF SYMBOLS 12 Speech recognition part 13 Response word generation part 14 Text speech synthesis part 15 Speaker 20 Pitch frequency analysis part 21 Psychological condition estimation part 22 Text conversion part 23 Speech rate measurement part 31 Word conversion part 32 Text division part 33 Candidate selection part 34 Word conversion Database (word conversion DB)
36 Text summary section 37 Text enhancement section

  Subsequently, the present invention will be described with reference to the first to third embodiments as preferred embodiments. In these embodiments, as abstracted in FIG. 1, in both cases, the target text is “spoken as speech” according to a parameter (psychological situation parameter) that represents the psychological situation of the listener. It comprises text conversion means (text conversion unit in FIG. 1) for transforming the text itself so that it becomes “intelligible text”.

[First Embodiment]
First, a first embodiment of the present invention in which text conversion is performed using a user's urgency (degree of urgency) as a parameter representing a user's psychological situation will be described. FIG. 2 is a block diagram showing the configuration of the text conversion apparatus according to the first embodiment of the present invention.

  Referring to FIG. 2, the text conversion apparatus according to the first embodiment of the present invention includes a voice input unit 11 such as a microphone, a pitch frequency analysis unit 20, a psychological situation estimation unit 21, a text conversion unit 22, It is configured with. The processing means of these text conversion apparatuses can be realized by a program that causes a computer constituting the text conversion apparatus to execute each process described later.

  The pitch frequency analysis unit 20 is a means for analyzing the voice uttered by the user input from the voice input unit 11 and obtaining the pitch frequency.

  The psychological situation estimation unit 21 is a means for obtaining a parameter x1 representing the degree of urgency of the user from the average value of the pitch frequency of the user voice and outputting the parameter x1 to the text conversion unit 22.

  FIG. 3 is a diagram showing a map for obtaining the urgency level x1 of the user from the average value of the pitch frequency. In the example of FIG. 3, the higher the average value of the pitch frequency is, the higher the user's urgency level x1 is. The curve of the monotonically increasing relationship (strictly speaking, when the average value of the pitch frequency exceeds the first threshold th1). When the user's urgency level x1 increases rapidly and the average value of the pitch frequency exceeds the second threshold th2, the S-shaped curve gradually increases again. This is because when the pitch frequency is high, it is possible to estimate that the urgency level of the user is high because the voice is uttered.

  The text conversion unit 22 is a means for generating an output text by converting the input text based on the score according to the user's urgency level x1 obtained as described above. The score or the total score in the present embodiment is an index representing the ease of understanding as a voice.

  FIG. 4 is a diagram showing a detailed configuration of the text conversion unit 22. The text conversion unit 22 includes a word conversion unit 31, a text division unit 32, a candidate selection unit 33, and a word conversion database (word conversion DB) 34.

  The word conversion unit 31 uses the word pairs registered in the word conversion DB 34 to obtain word conversion candidate groups that are all sets of text candidates that can be changed and are included in the input text having a length L, and the respective conversion scores. Output.

  The word conversion DB 34 records one or more pairs of words that have substantially the same meaning (the sentence meaning does not change even if they are replaced), and a conversion score S1 (i) when the words are converted by each word pair i. Has been. FIG. 5 is an example of word pairs and conversion scores registered in the word conversion DB 34. The conversion score can be set to be low for an input word having a homonym, and to be high for an output word having no homonym. This is because an input word in which a homonym is present (“personal computer” in FIG. 5 and “patker” each have a homonym of “PC”) is output word (in FIG. 5). “PC” and “Pokécon” do not have homonyms.

  The text dividing unit 32 converts each text of the input word conversion candidate group into lengths L (1), L (2),. . . A text conversion candidate group that is all combinations divided into N division units of L (N) is output.

  For example, when the input text is divided using reading marks, when M reading marks can be inserted, division of 2 M power types is possible.

  The text lengths L and L (1) to L (N) can be easily obtained and will be described as using the number of characters correlated with the pronunciation time length. If it can be obtained, the number of mora more strongly correlated with the pronunciation duration can be used.

  The candidate selection unit 33 selects a candidate in which y1 = x1− (α1 * S1 + α2 * S2) is positive and minimum among all combinations of text conversion candidates output by the text dividing unit 32, and the corresponding converted text Is output. Here, α1 and α2 are predetermined constants.

  Here, S1 calculated for each word conversion candidate is the sum of the conversion scores S1 (i) of the words used for conversion.

  Further, S2 calculated for each text conversion candidate is obtained by S2 = L ^ 2-Σ (L (i) * L (i)). The S2 obtained in this way becomes smaller as the number of divisions is smaller, and as the phrase length after conversion and division is uniform.

  FIG. 6 shows a result of calculating a score (overall score) for the input text “I bought a personal computer” using S1 and S2. In the example of FIG. 6, α1 = 10 and α2 = 1 are set as the constants α1 and α2.

  A method for calculating a score will be described with reference to FIG. For example, in the case of word conversion “none” for candidate number 1 and text division “none”, S1 = 0 (no conversion), S2 = 20 ^ 2− (20 ^ 2) = 0, and the total score is It is calculated as α1 × 0 + α2 × 0 = 0.

  Similarly, the word conversion “a” for candidate number 2 (in the case of “personal computer” in FIG. 5 converted to “personal computer” and text division “none”, S1 = 50, S2 = 20 ^ 2- (13 ^ 2 ) = 231, and the total score is calculated as α1 × 50 + α2 × 231 = 731.

  Similarly, the word conversion “b” of candidate number 3 (in the case of “personal computer” in FIG. 5 converted to “PC” and text division “none”, S1 = 50, S2 = 20 ^ 2- (13 ^ 2 ) = 231, and the total score is calculated as α1 × 50 + α2 × 231 = 731.

  If the criterion for selecting a candidate for which y1 = x1− (α1 * S1 + α2 * S2) of the candidate selection unit 33 using the total score is positive and minimum is applied, when the user's urgency level x1 is extremely high, the candidate The text conversion candidate of number 2 is selected. If the user's urgency level x1 is not remarkably high but is a certain value or more, the text conversion candidate with candidate number 3 is selected. When the user's urgency level x1 is low, the text conversion candidate with candidate number 1 is selected. That is, when the user's urgency level x1 is high, the candidate number 2 is selected with a short synonym of “I bought a personal computer” and a short paraphrase.

  The total score becomes higher every time the text is divided. For example, each of the text conversion candidates of candidate numbers 4 to 12 in FIG. 6 is more than the text conversion candidates of candidate numbers 1 to 3 that have been subjected to the same word conversion. The overall score is also high. In a state where all text conversion candidates are obtained, when the user's urgency level x1 is 200, candidate number 7 (total score = 159, y1 = 41) obtained by dividing the input text once is selected. Similarly, when the user's urgency level x1 is increased to 500, candidate number 3 (total score = 479, y1 = 21) obtained by performing word conversion so as to shorten the read-out sentence is selected. Further, when the user's urgency level x1 is further increased to 900, the candidate number 11 (total score = 855, y1 = 45) that is further finely divided is selected.

  As described above, a user with a high degree of urgency generates an output text that does not include synonyms as much as possible (easy to understand) and is finely divided (easy to hear).

  In the present embodiment, description has been made assuming that all candidates that can be selected are listed in advance, and selection is performed. However, the user's urgency level x1 is input to the word conversion unit 31 and the text division unit 32, and is not required at each stage. Simple candidates may be deleted or an optimal candidate may be selected. For example, when the user's urgency level x1 is high, only the text conversion candidates that have undergone conversion with a high score S1 are output, thereby reducing the load and processing time of the text dividing unit 32 and candidate selecting unit 33. Is possible.

[Second Embodiment]
Next, a second embodiment of the present invention in which text conversion is performed using a user's urgency level (immediate degree) as a parameter representing the user's psychological situation will be described. FIG. 7 is a block diagram showing the configuration of the text conversion apparatus according to the second embodiment of the present invention.

  Referring to FIG. 7, a text conversion apparatus according to the second embodiment of the present invention includes a voice input unit 11 such as a microphone, a voice recognition unit 12, a response message generation unit 13, an utterance speed measurement unit 23, A psychological situation estimation unit 21, a text conversion unit 22, a text speech synthesis unit 14, and a speaker 15 are configured. The processing means of the speech recognition unit 12, the response message generation unit 13, the speech rate measurement unit 23, the psychological situation estimation unit 21, the text conversion unit 22, and the text speech synthesis unit 14 constitutes a text conversion device. It can be realized by a program that causes a computer to execute each process described later.

  The voice recognition unit 12 is a unit that recognizes the voice input from the microphone 11 and outputs the voice to the response message generation unit 13.

  The response word generation unit 13 is a unit that generates a word that responds to the content of the user's utterance recognized by the voice recognition unit 12 and outputs it to the text conversion unit 22 as input text.

  The utterance speed measuring unit 23 is a means for measuring the utterance speed of the voice uttered by the user. The sound input from the microphone 11 is also input to the speech rate measuring unit 23, and the speech rate of the speech uttered by the user is measured.

  The psychological situation estimation unit 21 outputs a numerical value x2 representing the degree of urgency based on the value of the utterance speed measured by the utterance speed measurement unit 23.

  Here, the numerical value x2 representing the degree of urgency can be obtained from a relationship given in advance so as to have a monotonically increasing relationship with the speech rate value (unit: mora per second).

  The text conversion unit 22 is a means for generating an output text by converting the input text based on the score according to the user's degree of urgency x2 obtained as described above. The score or the total score in the present embodiment is an index representing the ease of understanding as a voice.

  FIG. 8 is a diagram showing a detailed configuration of the text conversion unit 22. The text conversion unit 22 includes a word conversion unit 31, a text summarization unit 36, a candidate selection unit 33, and a word conversion database (word conversion DB) 34.

  The word conversion unit 31 uses the word pairs registered in the word conversion DB 34 to output word conversion candidate groups that are all the sets of changeable text candidates included in the input text of length L.

  As in the first embodiment, one or more pairs of words having substantially the same meaning are recorded in the word conversion DB 34.

  In the present embodiment, the score S1 calculated for each word conversion candidate is obtained as S1 = L11−L12 from the number L11 of text before conversion and the number L12 of text after conversion by the word conversion unit 31. And

  The text summarizing section 36 summarizes the text of the input word conversion candidate group having a length L21 and outputs a summary text having a length L22. When a plurality of summary candidates can be generated by the text summarizing unit 36, all of them are included in the text conversion candidate group.

  The score S2 calculated for each text conversion candidate is obtained by S2 = L21−L22.

  The candidate selection unit 33 selects a candidate in which y2 = x2− (α1 * S1 + α2 * S2) is positive and minimum among all combinations of the text conversion candidates output from the word conversion unit 31 and the text summarization unit 36. And output. However, when y2 of all the text conversion candidates becomes negative, the candidate selection unit 33 selects and outputs a candidate that maximizes S1 + S2.

  FIG. 9 shows the result of calculating the score (total score) for the input text “My personal computer has been broken” using S1 and S2. In the example of FIG. 9, α1 = 1 and α2 = 1 are set as the constants α1 and α2 in the calculation formula of y2.

  A score calculation method will be described with reference to FIG. For example, in the case of word conversion “none” for candidate number 1 and text summary “none”, S1 = 0 (no shortening due to conversion), S2 = 0 (no shortening due to summary), and the total score is calculated as 0. Is done.

  Similarly, the word conversion “a” of candidate number 2 (in the case of “personal computer” in FIG. 5 converted to “personal computer” and the text summary “none” is calculated as S1 = 7, S2 = 0, and the total score is 7 is calculated.

  Similarly, in the case of the word conversion “b” of candidate number 3 (“personal computer” in FIG. 5 is converted to “PC” and the text summary is “none”, S1 = 9 and S2 = 0 are calculated, and the total score is 9 is calculated.

  When the criterion of selecting a candidate for which y2 = x2− (α1 * S1 + α2 * S2) of the candidate selection unit 33 using the total score is positive and minimum is applied, when the user's urgency level x2 is extremely high (frequency) 9 or more), the text conversion candidate with the shortest candidate number 3 among the candidate numbers 1 to 3 is selected. When the user's urgency level x2 is not remarkably high but is a certain value or more (frequency 7 or more and less than 9), the text conversion candidate of candidate number 3 is selected. When the user's urgency level x2 is low (frequency less than 7), the text conversion candidate with candidate number 1 is selected. That is, when the user's urgency level x2 is high, a candidate that is paraphrased shortly is selected by the word conversion of candidate number 3 "My PC has been broken."

  The total score becomes higher as the effect of text summarization becomes larger. For example, each of the text conversion candidates of candidate numbers 4 to 9 in FIG. 6 is the text conversion candidate of candidate numbers 1 to 3 obtained by performing the same word conversion. The overall score is higher than. In a state where all text conversion candidates are obtained, if the user's urgency level x2 is 20, the candidate number 9 (total score = 18, y2 = 2) is selected.

  As described above, in the present embodiment, when it is determined that the degree of urgency is high, it is possible to generate a sentence that is shorter and highly likely to be transmitted in a short time.

  In the present embodiment, it has been described that selection is performed after all possible candidates are listed. However, the user's urgency level x2 is input to the word conversion unit 31 and the text summarization unit 36, and is not required at each stage. Simple candidates may be deleted or an optimal candidate may be selected. For example, when the user's urgency level x2 is high, only the text conversion candidates that have undergone conversion with a high score S1 are output, thereby reducing the load and processing time of the text summarization unit 36 and candidate selection unit 33. Is possible.

  In addition, the numerical value x2 representing the degree of urgency of the user is not limited to the above, and can be obtained by the following methods.

  For example, the numerical value x2 representing the degree of urgency is obtained as a monotonically increasing relationship with the corresponding value by inputting the moving speed (vehicle speed or driving wheel rotational speed) of a vehicle such as an automobile on which the user is boarding (driving). .

  Also, for example, the numerical value x2 representing the degree of urgency is obtained when the brake operation of the automobile is input, the value of x2 is increased when the user driving the automobile depresses the brake, and the acceleration of the movement of the brake pedal is large. , X2 can be obtained by further increasing the value.

[Third Embodiment]
Next, a third embodiment of the present invention in which text conversion is performed using a user's concentration degree (concentration degree) as a parameter representing the user's psychological situation will be described. FIG. 10 is a block diagram showing the configuration of the text conversion apparatus according to the third embodiment of the present invention.

  Referring to FIG. 10, the text conversion device according to the third exemplary embodiment of the present invention includes a voice input unit 11 such as a microphone, a voice recognition unit 12, a response message generation unit 13, a speech rate measurement unit 23, A psychological situation estimation unit 21, a text conversion unit 22, a text speech synthesis unit 14, and a speaker 15 are configured. As in the second embodiment, the processing means of the text conversion apparatus of this embodiment can be realized by a program that causes a computer constituting the text conversion apparatus to execute each process described later.

  In the present embodiment, the psychological situation estimation unit 21 outputs a value x3 indicating the user's concentration level from the user's utterance speed, and the text conversion unit 22 performs text conversion using the value x3 indicating the user's concentration level. The other elements are the same as those in the second embodiment described above, and the differences will be mainly described.

  The psychological state estimation unit 21 obtains the user concentration degree x3 from the temporal variation component of the utterance speed value. Specifically, the fluctuation component Vdiff = Vmax−Vmin is calculated from the maximum value Vmax and the minimum value Vmin of the speech rate.

  When the value of the temporal variation component Vdiff of the utterance speed value is large, the psychological situation estimation unit 21 determines that there is a high possibility of being distracted by things other than dialogue and is a numerical value indicating the degree of concentration. x3 is output.

  Therefore, the numerical value x3 representing the degree of concentration can be obtained from a relationship given in advance so as to have a monotonously decreasing relationship with the time variation component value Vdiff of the speech rate value.

  The text conversion unit 22 is means for converting the input text based on the score according to the user concentration x3 obtained as described above, and generating the output text.

  FIG. 11 is a diagram showing a detailed configuration of the text conversion unit 22. The text conversion unit 22 includes a word conversion unit 31, a text enhancement unit 37, a candidate selection unit 33, and a word conversion database (word conversion DB) 34.

  The word conversion unit 31 uses the word pairs registered in the word conversion DB 34 to output word conversion candidate groups that are all the sets of changeable text candidates included in the input text of length L.

  In the word conversion DB 34, as in the first embodiment, one or more pairs of words having substantially the same meaning and a conversion score S1 (i) when the word is converted by each word pair i are recorded. Yes.

  Here, S1 calculated for each word conversion candidate is the sum of the conversion scores S1 (i) of the words used for conversion.

  The text emphasizing unit 37 extracts an important word from the text of the input word conversion candidate group having a length L21, and generates an output text having a length L22 in which the important word is repeated an arbitrary number of times (phrase repetition processing). For example, for the input text “Please press the B button next”, the text emphasizing unit 37 extracts the “B button” as an important word, and repeats the important word twice with a punctuation mark. "B button, please press B button". When the input text includes a plurality of important words, the text emphasizing unit 37 outputs all combinations of patterns obtained by repeating each important word as a text conversion candidate group.

  The important word candidates may be defined in advance in the text emphasizing unit 37, or the object word or the like may be extracted as the important word according to a certain rule.

  The score S2 calculated for each text conversion candidate is obtained by S2 = L22−L21.

  The candidate selection unit 33 determines that y3 = (1 / x3) − (β1 * S1 + β2 * S2) is positive and minimum among all combinations of the text conversion candidates output by the word conversion unit 31 and the text enhancement unit 37. Select the candidate to be output. However, when y3 of all the text conversion candidates is negative, the candidate selection unit 33 selects and outputs a candidate having the maximum S1 + S2.

  A method for calculating a score in this embodiment will be described. For example, in the case of word conversion “none” and text enhancement “none”, S1 = 0 (no conversion) and S2 = 0 (no enhancement) are calculated, and the total score is calculated as zero.

  On the other hand, word conversion such as conversion of “personal computer” to “personal computer” in FIG. 5 is performed, and in the case of text emphasis “none”, S1 = 50 and S2 = 0 are calculated, and β1 and β2 are set to 1, respectively. In this case, the total score is calculated as 50.

  On the other hand, in the case where word conversion such as conversion of “personal computer” in FIG. 5 to “personal computer” is performed and the text emphasis “button B” is repeated twice, S1 = 50 and S2 = 4 are calculated, and β1 , Β2 is 1, and the total score is calculated as 54.

  When the above-described candidate selection unit 33 using the total score is applied to a criterion for selecting a candidate where y3 = (1 / x3) − (β1 * S1 + β2 * S2) is positive and minimum, the user concentration level x3 is low. Sometimes, a text conversion candidate that performs both the word conversion and text emphasis is selected. On the other hand, when it is determined that the user's concentration x3 is high, a text conversion candidate that is not subjected to the word conversion or text emphasis is selected.

  As described above, in this embodiment, when it is determined that the user's concentration level is low, it is possible to generate a more verbose but easy-to-understand expression sentence.

  In this embodiment, the selection is made after all possible candidates are listed in advance. However, the user's concentration x3 is input to the word conversion unit 31 and the text emphasizing unit 37, and is unnecessary at each stage. Simple candidates may be deleted or an optimal candidate may be selected. For example, when the degree of user concentration x3 is low, only the text conversion candidates that have undergone conversion with a high score S1 are output, thereby reducing the load and processing time of the text enhancement unit 37 and candidate selection unit 33. Is possible.

  Further, the numerical value x3 representing the degree of user concentration is not limited to the above, and can be obtained by the following methods.

  For example, the numerical value x3 representing the concentration level is obtained by measuring and inputting the electrical resistance of the user's skin to estimate the amount of sweating of the user as a value that has a monotonous decrease relationship with the electrical resistance. It can be obtained from the relationship that the degree of concentration is high.

  Further, for example, the numerical value x3 representing the concentration degree can be obtained from the relationship that the concentration degree is high when the number of breaths per hour is small by measuring and inputting the respiration of the user.

  Further, for example, the numerical value x3 representing the degree of concentration can be obtained from the relationship that the degree of concentration is high when the number of pulsations per hour is large by measuring and inputting the user's pulse.

  The preferred embodiments of the present invention have been described above. However, the present invention is not limited to the above-described embodiments, and further modifications, replacements, and replacements may be made without departing from the basic technical idea of the present invention. Adjustments can be made. Further, for example, in the above-described second embodiment, it has been described that the score from the viewpoint of whether or not the converted word has a synonym is not used, but by appropriately correcting this score and adding it to the total score It is possible to output a voice that is easy to be transmitted to an imminent user.

Furthermore, in the first to third embodiments described above, the text conversion based on the user's urgency level, urgency level, and concentration level has been described, but the user urgency level of the above-described first to third embodiments, It is also possible to perform text conversion based on the degree of urgency and the degree of concentration, respectively, and select a text suitable for the psychological situation of the user from the text conversion and utter it. Of course, it is possible to perform text conversion not only with the user's urgency level, urgency level, and concentration level but also with parameters representing other psychological situations.
The parameters representing various psychological situations such as the user's urgency level, urgency level, and concentration level, input / output text, and text conversion program may be anything that can be handled as a physical or electrical signal by the computer. . The text conversion program causes a computer in which parameters and text representing the psychological situation are input to function as physical means for outputting the converted text.

The present invention can be used for various applications such as a speech synthesizer, a speech dialogue system, a speech automatic response device, an intelligent robot, etc., which changes the utterance text by combining with a text-to-speech synthesizer. it can.
It should be noted that the embodiments and examples can be changed and adjusted within the scope of the entire disclosure (including claims) of the present invention and based on the basic technical concept. Various combinations and selections of various disclosed elements are possible within the scope of the claims of the present invention. That is, the present invention of course includes various variations and modifications that could be made by those skilled in the art according to the entire disclosure including the claims and the technical idea.
[Appendix 1-Amended claim 3 under Article 34 of the Convention]
The text conversion apparatus according to claim 1, wherein a user's urgency level is used as a parameter representing the user's psychological state.
[Appendix 2-Amended claim 4 under Article 34 of the Convention]
The text conversion apparatus according to claim 1, wherein the user's urgency level is used as a parameter representing the user's psychological state.
[Appendix 3-Amended claim 5 under Article 34 of the Convention]
The text conversion apparatus according to claim 1, wherein a user concentration level is used as a parameter representing the user's psychological state.
[Appendix 4-Amended claim 6 under Article 34 of the Convention]
The text conversion device according to claim 3, wherein the urgency level of the user is replaced with an average value of pitch frequencies of voices uttered by the user.
[Appendix 5-Amended claim 7 under Article 34 of the Convention]
The text conversion device according to claim 4, wherein the degree of urgency of the user is replaced by a speed of voice uttered by the user.
[Appendix 6-Amended claim 8 under Article 34 of the Convention]
The text conversion apparatus according to claim 5, wherein the user's concentration degree is replaced with a temporal variation component of a speed of voice uttered by the user.
[Appendix 7-Amended claim 9 under Article 34 of the Convention]
Create multiple text conversion candidates by replacing a word in the input text with another word,
The text conversion apparatus according to claim 1, wherein a score is given to each of the text conversion candidates according to the number of homonyms that the replaced word has.
[Appendix 8-Claim 10 after amendment under Article 34 of the Convention]
Create multiple text conversion candidates by replacing a word in the input text with another word,
The score is given to each of the text conversion candidates according to the length of time when each of the text conversion candidates is read out or the length of the sentence of each of the text conversion candidates. 8. The text conversion device according to any one of 8.
[Appendix 9-Amended claim 11 under Article 34 of the Convention]
Create multiple text conversion candidates by dividing the input text into multiple units,
The score is given to each text conversion candidate according to the number of division units included in each text conversion candidate or the length of each division unit. Text converter.
[Appendix 10-Claim 12 after amendment under Article 34 of the Convention]
By extracting one or more important words from the input text and performing a conversion operation of overlapping the important words twice or more, a plurality of text conversion candidates are created,
9. The text conversion apparatus according to claim 1, wherein a score is given to each text conversion candidate according to the number of times of the conversion operation.
[Appendix 11-Amended claim 15 under Article 34 of the Convention]
14. A speech output device comprising: the text conversion device according to claim 1; and a text-to-speech synthesizer that reads a text output from the text conversion device.
[Appendix 12-Amended claim 16 under Article 34 of the Convention]
A robot comprising the audio output device according to claim 15, wherein the robot outputs audio in accordance with a listener's psychological situation.
[Appendix 13-Claim 19 after amendment under Article 34 of the Convention]
Create multiple text conversion candidates by replacing a word in the input text with another word,
18. The text conversion method according to claim 17, wherein a score is given to each of the text conversion candidates in accordance with the number of homonyms that the replaced word has.
[Appendix 14-Amended claim 20 under Article 34 of the Convention]
Create multiple text conversion candidates by replacing a word in the input text with another word,
The score is given to each of the text conversion candidates according to a time length when the text conversion candidates are read out or a sentence length of each of the text conversion candidates. Text conversion method.
[Appendix 15-Amended claim 21 under Article 34 of the Convention]
Create multiple text conversion candidates by dividing the input text into multiple units,
The text conversion method according to claim 17, wherein a score is given to each text conversion candidate according to the number of division units included in each text conversion candidate or the length of each division unit.
[Appendix 16-Claim 22 after amendment under Article 34 of the Convention]
By extracting one or more important words from the input text and performing a conversion operation of overlapping the important words twice or more, a plurality of text conversion candidates are created,
The text conversion method according to claim 17, wherein a score is given to each text conversion candidate according to the number of times of the conversion operation.
[Appendix 17-Amended claim 25 under Article 34 of the Convention]
Create multiple text conversion candidates by replacing a word in the input text with another word,
The text conversion program according to claim 23, wherein a score is given to each of the text conversion candidates according to the number of homonyms that the replaced word has.
[Appendix 18-Claim 26 after amendment under Article 34 of the Convention]
By replacing a word in the input text with another word, a plurality of text conversion candidates are created, and the time length when each of the text conversion candidates is read out or the length of the sentence of each text conversion candidate is set. The text conversion program according to claim 23, wherein a score is given to each of the text conversion candidates accordingly.
[Appendix 19-Amended claim 27 under Article 34 of the Convention]
Create multiple text conversion candidates by dividing the input text into multiple units,
The text conversion program according to claim 23, wherein a score is given to each text conversion candidate in accordance with the number of division units included in each text conversion candidate or the length of each division unit.
[Appendix 20-Amended claim 28 under Article 34 of the Convention]
By extracting one or more important words from the input text and performing a conversion operation of overlapping the important words twice or more, a plurality of text conversion candidates are created,
The text conversion program according to claim 23, wherein a score is given to each of the text conversion candidates according to the number of times of the conversion operation.
[Appendix 21-Amended claim 29 under Article 34 of the Convention]
29. A voice output program for causing the computer to further execute a process of converting a text to be output into a voice by a text-to-speech synthesis technique using the text conversion program according to any one of claims 23, 25 to 28.

Claims (10)

By replacing a word in the text with a word pair that does not change the meaning even if it is replaced with a parameter that represents the user's psychological state and the text, the range does not change the meaning of the input text, When creating a plurality of text conversion candidates and listening to the output text as speech using the score when the text is converted using the word pairs set for each word pair for each text conversion candidate A text conversion device that performs a conversion operation of input text by obtaining a score indicating the ease of understanding and selecting a text conversion candidate having a score that matches the input parameter.   The text conversion apparatus according to claim 1, wherein an average value of pitch frequencies of speech uttered by the user is used as a parameter representing the psychological state of the user.   The text conversion apparatus according to claim 1, wherein a speed of a voice uttered by the user is used as a parameter representing the psychological state of the user.   The text conversion apparatus according to claim 1, wherein a temporal variation component of a speed of voice uttered by the user is used as a parameter representing the psychological state of the user. The text conversion device according to any one of claims 1 to 4, wherein the score is set so as to promote replacement with a word in which no homonym objection word exists. The score is given to each text conversion candidate according to the length of time when each text conversion candidate is read out or the length of a sentence of each text conversion candidate. The text conversion apparatus as described in any one. Instead of replacing words in the text with word pairs that do not change the meaning of the text,
Create multiple text conversion candidates by dividing the input text into multiple units,
The text according to any one of claims 1 to 5, wherein a score is given to each text conversion candidate according to the number of division units included in each text conversion candidate or the length of each division unit. Conversion device. Instead of replacing words in the text with word pairs that do not change the meaning of the text,
By extracting one or more important words from the input text and performing a conversion operation of overlapping the important words twice or more, a plurality of text conversion candidates are created,
6. The text conversion apparatus according to claim 1, wherein a score is given to each of the text conversion candidates according to the number of times of the conversion operation. Based on the user's voice or the user's operation content, a psychological situation estimation unit that outputs a parameter for estimating the user's psychological situation;
A word conversion candidate group is generated by replacing a word in the text using a word pair whose sentence meaning does not change even if it is replaced, and set for each word conversion candidate in each text conversion candidate included in the text conversion candidate group By assigning a score using the score when the text is converted using the word pair, and selecting a text conversion candidate to which a score that matches the parameter for estimating the psychological state of the user is selected. A text converter that replaces words in the input text with synonyms;
A text conversion device comprising: A text conversion method by a text conversion device,
Inputting parameters representing the user's psychological state and text;
A plurality of text conversion candidates are generated from the text by replacing a word in the text with a word pair whose sentence meaning does not change even if replaced ,
For each of the text conversion candidates, obtain a score indicating ease of understanding when the output text is received as speech using the score when the text is converted using the word pair set for each word pair , Selecting a text conversion candidate having a score that matches the input parameter, thereby converting the input text within a range that does not change the meaning of the sentence based on the input parameter.

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