JP2000259165A - Data reader and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To report a lot of routine data in voice in a short time without getting tired by storing plural model sentences for embedding the routine data, and synthesizing sentences while changing the model sentence to be embedded for each piece of routine data. SOLUTION: A model sentence selecting part 1 inputs routine data from a routine data storage part 1-1 and selects a model sentence according to a predetermined prescribed selection method. Plural model sentences are stored in a model sentence storage part 1-2 while making different contents in the fixed character parts of sentences so as to embed all the respective routine data. In the case of reading routine data expressed as a table or the like, the sentence in the same format is not repeatedly read but different sentences can be read for each piece of routine data, overlapped data can be simultaneously read or only required information can be first heard. Therefore, a listener can listen to the required information in a short time without getting tired.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of synthesizing and reading out a plurality of fixed data when there are a plurality of fixed data having a specific format including a plurality of data such as weekly weather forecast data. And a recording medium on which a computer program for reading fixed form data is recorded.

[0002]

2. Description of the Related Art A conventional data reading apparatus reads a fixed form data, creates a sentence by embedding the fixed form data in a specific sentence example, converts it into an intermediate notation representing reading, accent, and intonation, and synthesizes a voice. Output from a speaker or the like. In this case, since the text is created by embedding the standard data in the same sentence example, if there are many standard data, only the data part is different,
It becomes a repetition of monotonous sentences. Therefore, if there is a lot of standard data, the listener is often frustrated or tired while listening, and it often takes a considerable amount of time to obtain all the necessary information.

[0003]

In recent years, the performance of CPUs of computers, the integration of memories, and the cost of them have been rapidly increasing, and computers with small size, high performance, and large capacity memory have become increasingly smaller. Is becoming Therefore, it is possible to incorporate a speech synthesizer that requires a high-performance CPU or a large-capacity memory, and various devices that provide information by voice are rapidly spreading.

[0004] With the rapid spread of devices incorporating a speech synthesizer, more and more people are receiving opportunities to provide information by speech-synthesized speech. However, since audio information needs to be conveyed by voice one by one in order, the amount of information that can be received per unit time is very small as compared with visual information. Therefore, even if you can read necessary information at a glance, if you receive it as audio information, it takes a long time to get the necessary information because it reads out the information by voice in order .

[0005] The most prominent example is information represented by a table having a number of fixed data. The information shown in the table can be seen in a short time when viewed with the naked eye, and it is easy to acquire only the necessary information, but when converting it to audio information and listening, the information you want to know is displayed. At the end of the process, you have to be patient and listen to unnecessary information, and even if you need all the information, the same pattern is repeated many times. Listening time is long and sentences are monotonous.

The service of providing information by voice was initially limited to a device such as a telephone having only a voice output device, but recently has a display screen such as a display such as a car navigation system. However, because it is dangerous to watch the screen while driving, there is an increasing number of devices that provide information not only on the screen but also by voice.

[0007] In order to further spread the use of devices that provide voice information by voice synthesis, there is a demand for a technical means for transmitting a number of standard data in a short time and without getting tired.

[0008]

SUMMARY OF THE INVENTION According to the present invention, a plurality of fixed data having a specific format composed of one or more data that can be represented in a table is not read out by repeating the same sentence, but the sentence is changed. Regarding the repetitive portion, the portion that can be omitted is omitted or the data order is changed, so that information can be read aloud in a shorter time without getting tired.

The data reading device according to the present invention comprises:
A text-to-speech device that synthesizes a sentence based on fixed-form data having a specific format composed of one or more data and outputs a voice, a sentence-example storage unit that stores a plurality of sentence examples for embedding the fixed-form data, and reads the fixed-form data. A sentence synthesizing unit for synthesizing a sentence by changing a sentence example to be embedded for each of the fixed data.

[0010] With this configuration, instead of repeating the same sentence only by changing the data portion as in the related art, the user can listen to the information by audio output of a different sentence for each fixed data, so that the user can hear the audio information without getting bored.

Further, a data reading device according to the present invention synthesizes a sentence based on fixed data having a specific format composed of one or more data, and outputs a voice. The data reading device stores a plurality of the fixed data. A fixed form data storage unit, a sentence example storage unit for storing a plurality of sentence examples for embedding the fixed form data,
A sentence example selecting section for selecting a sentence example to be embedded for each of the fixed form data, a sentence synthesizing section for synthesizing a document based on the fixed form data and the selected sentence example, and analyzing the synthesized document, And a speech synthesizer for synthesizing and outputting speech based on the intermediate notation.

With such a configuration, instead of repeating the same sentence only by changing the data portion as in the related art, the user can listen to the information by audio output with a different sentence for each fixed data, so that the user can hear the audio information without getting bored.

Further, a data reading device according to the present invention synthesizes a sentence based on fixed data having a specific format composed of one or more data, and outputs a voice. The data reading device stores a plurality of the fixed data. A fixed form data storage unit, a sentence example storage unit that stores a plurality of sentence examples for embedding the fixed form data in an intermediate notation format for expressing voice, and a sentence example to be embedded for each of the fixed form data from the sentence example storage unit. A sentence example selecting unit for selecting by selecting, a fixed form data conversion unit for converting the fixed form data into intermediate notation, based on the converted fixed form data and the selected sentence example,
A text synthesizing unit for synthesizing a document and a voice synthesizing unit for synthesizing and outputting speech based on the synthesized text are provided.

With this configuration, since the sentence example is in the intermediate notation from the beginning, when reading the fixed data, only the fixed data needs to be converted to the intermediate notation, and the syntax analysis is not required, and the intermediate notation can be changed. Since it becomes easy, the processing speed can be improved.

Further, the data reading apparatus according to the present invention is provided with a duplication check flag indicating whether or not each of the fixed data is subjected to a duplication check, and the sentence example storage unit collects the overlapping portions of the fixed data. The sentence example selecting unit has a function of storing a sentence example to be expressed in the form of an expression, and checking a duplicated portion of the standard data based on the duplication check flag, and selecting a sentence example that combines the corresponding duplicated portions.

With this configuration, if the same type of the same data is included in the fixed data, a sentence can be created by combining the same data, so that the sentence can be shortened and the sentence can be changed. Without getting bored
Listen to audio information in less time.

Further, in the data reading apparatus according to the present invention, each data of the fixed form data includes a data set flag indicating a set of data to be read out collectively in the fixed form data, and the sentence example storage unit is provided for each data set unit. A plurality of sentence examples including only the data of the data set are stored, and the preceding sentence example selection unit has a function of reading all the fixed data collectively and selecting a corresponding sentence example in a specified data set unit. And

With this configuration, it is possible to collectively output data of high importance in a plurality of fixed data and output the data as voice, and to output the subsequent data as detailed data subsequently. You can listen first, and later information can be heard if you do not need it.

Also, a computer readable recording medium having recorded thereon a program to be executed by a computer according to the present invention is a step of synthesizing a sentence based on fixed data having a specific format consisting of one or more data, A computer-readable recording medium that records a program for causing a computer to execute the step of outputting a voice as a step of storing a plurality of example sentences for embedding the standard data, reading the standard data, reading the standard data, for each of the standard data The method is characterized in that the method includes a step of synthesizing a sentence by changing a sentence example to be embedded.

With this configuration, instead of repeating the same sentence only by changing the data portion as in the prior art, the user can listen to the information by voice output with a different sentence for each of the standard data. The device can be realized.

Further, a computer readable recording medium having recorded thereon a program to be executed by a computer according to the present invention is a step of synthesizing a sentence based on fixed data having a specific format consisting of one or more data, A computer-readable recording medium recorded with a program to be executed by a computer including a step of outputting a voice, a step of storing a plurality of the fixed data, and a step of storing a plurality of sentence examples for embedding the fixed data, Selecting from the stored sentence examples a sentence example to be embedded for each of the fixed-form data; synthesizing a document based on the fixed-form data and the selected sentence example; analyzing the combined document Converting to an intermediate notation for expressing speech; Characterized in that it comprises respectively the step of outputting the synthesized speech based on the notation.

With such a configuration, instead of repeating the same sentence only by changing the data portion as in the prior art, the user can listen to the information by audio output with a different sentence for each of the standard data. The device can be realized.

[0023]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The principle and basic operation flow of the present invention will be described with reference to a basic configuration diagram of the present invention shown in FIG. 1 and a flowchart showing a basic processing flow of FIG.

First, the sentence example selecting section 1 inputs the fixed form data from the fixed form data storage section 1-1 (step S1). If the fixed form data is not completed (step S2: NO), a predetermined predetermined form is set. A sentence example is selected by a selection method (step S3). If the fixed data has ended (step S2: YES), the processing ends.

Normal data and sentence examples are usually prepared in advance by a data provider. Therefore, in the basic configuration diagram of FIG. 1, an input unit is not provided, and it is assumed that they have already been registered. You may make it perform by providing an input part in a structure. The input of the standard data and the sentence example may be performed with a normal editor. Up to this step is a characteristic part of the present invention, and it is possible to read out different sentences using different sentence examples for each fixed data, without repeating the same sentence where the fixed data is changed only in the data portion As a result, the listener can hear the read-out information without getting bored.

The subsequent steps are the same as those of the conventional text-to-speech apparatus and take a general example, and are not limited to this pattern. You may use the structure of a speech-to-speech device. Sentence synthesis unit 2
Receives the fixed form data and the sentence example, and synthesizes a sentence by incorporating the fixed form data into the sentence example (step S4). When the sentence analysis unit 3 receives the synthesized sentence, the sentence analysis unit 3 performs morphological analysis and syntax analysis of the sentence using the morphological dictionary 3-1 and converts the sentence into an intermediate notation format representing speech (step S5). The speech synthesis unit 4 receives the intermediate notation, synthesizes speech using the speech unit dictionary 4-1 and reads out a sentence aloud (step S6).

Here, an example is given of what the intermediate notation is.

For example, if the synthesized sentence is a sentence "The weather on the eastern part of Kanagawa on July 13 will be cloudy after a sunny day. The probability of rain from 0:00 to 6:00 will be 20%." , The intermediate notation is "Kanakawa 'Ken_
Tobno, Shichigatsu_Jusa Ninichino_Tenkiwa, Halle'Nochi_Kumori 'desho. 'Regular' _Loku 'Jimedeno_A'Meno_Kaklitswa, Nizipase'
Nt_desho. ]. Katakana represents reading, "'" and "_" represent accent information,
"," Indicates that a pose is to be taken there. The intermediate notation given here is merely an example, and a notation different from the notation used here may be used.

[0029]

[Embodiment 1] A description will be given of an example in which a plurality of sentence examples having different contents of a sentence are prepared, and a sentence example is selected for each fixed data and read out by voice. Since the present embodiment is the same as the basic configuration diagram of FIG. 1, the detailed description of each functional part will be omitted, and the detailed functions of the sentence example selection unit 1 will be described.

A plurality of sentence examples are stored in the sentence example storage unit 1-2 in such a manner that all the data of the fixed form data can be embedded in the fixed character portion of the sentence with different contents. Since there are a plurality of methods for designating where in the sentence example each data of the fixed form data is to be embedded, some of the examples are given as weather data in which the fixed form data includes a district name, month, day, and weather.

First, the first pattern of the method of designating data in the sentence example is that the contents of the sentence example are “{1} {2} weather is {
3≫. ]. The number between the symbols ≪ and ≫ indicates the number of the standard data to be inserted. That is, {1} is the district name as the first data, {2} is the month and day as the second data, and {3} is 3
Represents the second data, weather. By doing this, you can find out in which position in the sentence example which data of the fixed form data should be placed, and not only create a sentence example in which the fixed character part of the sentence example is changed while the data order is unchanged, but also create a sentence example in which the data order is replaced. As a result, it is possible to add many different variations to the text to be read, and it is possible to make the listener hard to get tired of.

Next, as the second pattern of the method of specifying data in the sentence example, the first pattern makes it difficult to determine which data the numerical data points to when it is later corrected. Instead of representing the data only with numbers, add a comment to indicate which data the numbers represent, and the weather for {1: district name {2: month and day} will be {3: weather} . "To make it easier to understand what the variables are. Thereby, in addition to the advantage of the first pattern, the maintainability when adding or modifying a sentence example can be facilitated.

Next, as a third pattern of the data specification method in the sentence example, data in which data names to be applied in the order of the fixed form data are prepared, and “{district name}, {month date}, For example, "weather" may indicate what name each variable of the standard data is assigned to a variable. The symbols ≪ and を indicating a variable may be omitted as long as the separator between the variables is known.
It may be "area name, month, day, weather". The data designating the variable name to be assigned to each of the fixed data may be stored as the first fixed data in the fixed data storage unit 1-1, or may be set as the first fixed data in the sentence example storage unit 1-2. It may be stored as sentence example data, or may be input as a parameter of the program of the sentence example selection unit 1. This allows
Which data should be embedded where can be specified directly in the sentence example by data name. That is, when the data specifying the variable name is entered as the first sentence example data in the sentence example storage unit 1-2, the sentence example selection unit 1 reads the data specifying the variable name in the first sentence example of the sentence example. Of 1
The second data can be recognized as the district name, the second data as the month and day, and the third data as the weather, so in the sentence example, do not include the number indicating the data to be inserted,
"The weather on the month and day of the district name will be weather."
, Use the variable name specified in the first sentence of the sentence example. As a result, in the first sentence example, if only the variable name to be attached to each data of the fixed form data is specified, when creating the sentence example, there is no need to be aware of the data of the fixed form data. You will be able to add and modify in a natural way.

In this example, the variable name is inputted as the first data of the sentence example. However, this is because the variable name can be used as a general-purpose data reading device in which the reading data changes variously. If a fixed-form data reading device for a specific purpose is good, a variable name used in the fixed-form data may be defined and stored in the program.

Even if any of these patterns of sentence examples is used, not only various sentence examples in which parts other than variables are changed, but also the order of variables itself is arbitrary, so that various variations can be given to a document to be read. It becomes possible to make the listener hard to get tired of.

In addition, the fourth method of designating data in a sentence example
As a pattern of, when each data of the fixed form data is embedded in the sentence example in the order from the beginning, “≪≫≪≫≪≫
The weather will be ≪≫. ", The number indicating the data or the variable name may be omitted, and only the symbol indicating the position where the data is inserted may be used. However, this pattern cannot cope with a sentence example in which the order of data is changed.

In the case of the above-mentioned first and second patterns, the sentence example selecting section 1 prepares a data table (not shown) numbered sequentially from 1 and reads the fixed form data, and sorts each data in order. To be stored. In the case of the third pattern, the sentence example selecting unit 1 stores, in the data name column of a two-dimensional data table (not shown) including a data name and data, the fixed-form data storage unit 1-1 or the sentence example storage unit 1-2. When the data in which the first data name is listed is read, or a parameter representing the data is fetched, the data names are stored in order, and when the fixed form data is read, each data is read in order of the corresponding data name in the data table. Store in part. In the case of the fourth pattern, it is unnecessary to create a data table. Sentence example selector 1
Is sent in the form of a data table in the case of the first to third patterns.
In the case of the fourth pattern, the fixed data is passed as it is.

Next, the sentence example storage unit 1 stores
A sentence example is selected from a plurality of sentence examples. There are several possible methods, and an example of the method is given below. In the present embodiment, it is assumed that the sentence example storage unit 1-2 stores increasingly simplified sentence examples in order from the most polite sentence example.

The first method is a method in which the first sentence example to the last sentence example are used repeatedly and repeatedly.
This method reads the sentence example and the standard data in order from the beginning,
Both data are used as they are. If the number of fixed form data is larger than that of the sentence example, after reading the last sentence example, the process returns to the beginning of the sentence example and reads it. In this way, the sentence example is read while circulating until there is no more fixed data.
This makes it easier to use the same sentence continuously.

The second method is to determine the number of the sentence example to be used by generating a pseudo integer of a positive integer equal to or less than the number of sentence examples. At this time, a random number is stored several times in the past, and when the same random number as the stored random number is generated, the random number is calculated again until a random number that is not stored appears. It may not be used or repeated at short intervals. When using the third pattern of the data designation method in the above sentence example and storing data in which the data names are listed in the sentence example storage unit 1-2, the first data in the sentence example is the data name list. Since this is not a sentence example, a pseudo-random number of a positive integer equal to the number of the sentence example minus one is generated, and the sentence example to be used uses the pseudo-random number + 1st sentence example. In the first method, since the same sentence example is repeated at regular intervals, the next sentence example can be predicted if heard many times, or the most careful sentence example comes after the most simplified expression example, According to this method, it is possible to make it impossible to predict which sentence will come next.

A third method is to use a predetermined first sentence example only once, and to read out subsequent repeated example sentences by using the first method or the second method. It is. The first few sentences use sentence examples that use polite expressions, and after that, sentence examples with simplified expressions are stored. In order to indicate the first polite sentence and the simplified sentence to be repeated, information on the number of polite sentences is set in advance in the program of the sentence example selecting unit 1. However, for general purpose, it is preferable to provide a flag at the head of each sentence example as to whether or not the sentence example is a repeated sentence example. An example of a sentence example is shown in FIG. In this example, the first and second sentence examples are used only once at first, and the third and fourth sentence examples are repeated. For the listener, it is preferable that the sentences to be listened to at first be polite and progressively simplified. However, the first method may return from a simplified expression to a polite expression upon repetition, and the second method may start with a simplified expression or use a polite expression from the simplified expression. However, this method can avoid such a problem.

The first pattern is used as a method of designating data in a sentence example, the third pattern using pseudo random numbers is used as a method of selecting a sentence example, and a sentence in the case where there is a sentence example as shown in FIG. The flow of processing of the selection unit 1 (corresponding to the processing of steps S1 to S3 in FIG. 2) will be described with reference to the flowchart in FIG.

The sentence example selecting section 1 reads a sentence example (step S11), and determines whether or not a flag indicating whether the sentence example is a sentence example used repeatedly is set (step S1).
2) If the repetition flag is not set (step S12: NO), the template data is read (step S13), and if the template data is not completed (step S12).
14: NO) gives the sentence example and the fixed form data to the sentence synthesizing unit (step S15). Since the sentence example for which the repetition flag is not set is used only once, the process returns to step S11 to read the next sentence example. If the fixed data has ended (step S14: YES), the program ends.

If the repetition flag of the sentence example is set (step S12: YES), the sentence example is stored in the table, and the number of sentence examples is counted (step S16).
Then, the next sentence example is read (step S17). If all sentence examples for which the repetition flag is set are not read (step S18: N)
O) returns to step S16 and repeats until the sentence example ends.

When the example sentences to be repeatedly used are stored in the table, the fixed form data is read (step S19), and when the fixed form data is not completed (step S20: NO)
Generates a pseudo integer of a positive integer equal to or less than the count of the example sentences stored in the table, and selects which example sentence to use (step S21). The read fixed form data and the selected sentence example are transferred to the sentence synthesizing unit 2 (step S22), and the process returns to step S19 to read the next fixed form data.
When the standard data has been completed (step S20: YES)
Terminates the program.

[0046]

[Embodiment 2] Next, an embodiment in which sentence examples are stored in the form of intermediate notation, and only fixed-form data is converted to intermediate notation, thereby eliminating the need for text analysis.
This will be described with reference to FIG. The description of the same parts as those in FIG. 1 will be appropriately omitted.

In the present embodiment, the sentence example selecting unit 1 reads the fixed form data, performs a duplication check and the like, selects the sentence example, and then selects the sentence example. The fixed form data is passed to the fixed form data conversion unit 5. The fixed form data conversion unit 5 includes a fixed form data morphological dictionary 5
Using −1, each data of the received fixed form data is converted into an intermediate notation and passed to the text synthesizing unit 2. The sentence synthesis unit 2
From the received sentence example of the intermediate notation and the standard data, a sentence of the intermediate notation is synthesized, passed to the speech synthesizer 4, and read out as speech information.

The morphological dictionary for fixed data is a morphological dictionary 3
It is only necessary to store an intermediate notation of only morphemes included in the fixed form data. However, if there is no problem in the capacity of the hard disk, there is no problem even if the morphological dictionary 3-1 is used.

Regarding the data names in the sentence examples, the symbols ≪ and ≫ indicating that they are variable names may be left in the intermediate notation, but in order to make the variable names easy to understand, the intermediate notation is not used. Is more preferred.

According to the present embodiment, it is necessary to store the sentence example in the intermediate notation, and it is troublesome to directly create the sentence example in the intermediate notation as compared with the case of inputting a normal sentence. In this case, an ordinary sentence may be input first, and the process corresponding to the sentence analysis unit 3 described in the first embodiment may be executed to prepare a sentence example of the intermediate notation in advance. It is also conceivable that the fixed form data is set to an intermediate notation from the beginning.
In that case, the fixed form data conversion unit 5 of FIG. 5 becomes unnecessary.

The flow of processing according to the present embodiment will be described with reference to the flowchart of FIG.

When the fixed form data is input from the fixed form data storage section 1-1 (step S31), and the fixed form data is not completed (step S32: NO), a sentence example is selected from the sentence example storage section 1-2 by a predetermined method (step S32). Step S33).
When the fixed data is completed (step S32: YES)
Ends the processing. The fixed form data is passed to the fixed form data conversion unit 5 and converted into an intermediate notation (step S3).
4). Both the sentence example and the fixed form data are passed to the sentence synthesizing unit 3 in the form of an intermediate notation, and the sentence is synthesized (step S).
35). Based on the synthesized text, the voice synthesis unit synthesizes a voice and reads out the text (step S36).

As described above, according to the present embodiment, since the sentence example is in the intermediate notation from the beginning, only the data needs to be converted to the intermediate notation when reading the fixed data. Syntax analysis is not required, and a program for sentence analysis is not required.Since it is only necessary to prepare data for fixed data in the morphological dictionary, it is easy to change to intermediate notation, and the capacity of memory and storage devices is small. The processing speed can be improved.

[0054]

[Embodiment 3] Next, an embodiment in which overlapping portions of fixed data are read out collectively will be described with reference to FIG. The description of the overlapping part will be omitted as appropriate.

In the present embodiment, it is assumed that there is duplicate data that can be collectively expressed as fixed data. For example, taking a weekly weather forecast as an example, the standard data is: district name / month / day / weather / precipitation probability 1 / precipitation probability 2 / precipitation probability 3
・ Precipitation probability 4 ・ Predicted minimum temperature ・ Expected maximum temperature
Probability of precipitation until hour, Probability of precipitation from 6:00 to 12:00, 1
It represents the probability of precipitation from 2:00 to 18:00 and the probability of precipitation from 18:00 to 24:00. In the case of this data, with respect to the precipitation probabilities 1 to 4, if the same precipitation probabilities are continuous, it is possible to collectively express the portions. For example,
"The weather on {2} of {1} is {3}, the probability of precipitation from 0:00 to 6:00 is {4}, and from 6:00 to 12:00 is {5}, 12
6 hours from 18:00 to 18:00, 18:00 to 24:00
7≫, the expected minimum temperature is 8≪, and the expected maximum temperature is 9≪. ", The following seven sentence examples can be further considered depending on how the data of the precipitation probabilities from {4} to {7} overlap, so that a total of eight sentence examples can be created. The weather on {2} of {1} is {3}, the probability of precipitation from 00:00 to 12:00 is {4}, the probability of precipitation from 12:00 to 18:00 is {6},
From 18:00 to 24:00 is $ 7, and the expected minimum temperature is $ 8
≫ The expected maximum temperature will be ≪9≫. The weather on {2} is {3}, the chance of rain from 00:00 to 6:00 is {4}, and the probability of rain from 6:00 to 18:00 is {5}, 18
From the hour to 24:00, the expected minimum temperature will be $ 8, and the expected maximum temperature will be $ 9. The weather on {2} of {1} is {3}, the probability of precipitation from 0:00 to 6:00 is {4}, and from 6:00 to 12:00 is {5}, 12
From time to 24:00, the expected minimum temperature is $ 8, the expected maximum temperature is $ 9, and the expected maximum temperature is $ 9. The weather on {2} of {1} is {3}, the probability of precipitation from 00:00 to 12:00 is {4}, the probability of precipitation from 12:00 to 24:00 is {6},
The expected minimum temperature will be $ 8, and the maximum expected temperature will be $ 9. The weather on {2} of {1} is {3}, the chance of precipitation from 00:00 to 18:00 is {4}, the probability of precipitation from 18:00 to 24:00 is {7},
The expected minimum temperature will be $ 8, and the maximum expected temperature will be $ 9. The weather on {1} is {3}, the chance of rain from 00:00 to 6:00 is {4}, from 6:00 to 24:00 is {5}, the expected minimum temperature is {8}, and the expected maximum temperature. Would be {9}. The weather on {2} on {1} is {3}, the chance of rain from midnight to 24:00 is {4}, the lowest expected temperature is {8}, and the highest expected temperature is {9}.

Although it is possible to omit the data as described above within one set of data, the duplication check of the data is performed by 1
It is not necessary to limit the data to one fixed data, and a part common to a plurality of fixed data may be omitted. For example, in the case of the above-mentioned standard data of the weekly weather forecast, there is the standard data from Sunday to Saturday. In this case, the district name {1} is the same in any fixed data, and it is sufficient to read it out once at the beginning, and may be omitted in the second and subsequent readings. That is, since the example in which the district name {1} is omitted is added to the pattern of the eight example sentences, a total of 16 example sentences can be created. In this case, since the duplication of the data is checked over a plurality of fixed data, the read fixed data needs to be stored in a memory or the like.

Next, a method of checking for duplicate data will be described. The problem with the checking method is how to determine which data should be checked for duplication of which data.

The first method of determining data to be checked for duplication is a method of checking duplication by simply judging whether or not each data of fixed data is the same continuously. With this method, there is no need to indicate which data and which data should be checked, and it is sufficient to simply check whether the same data is continuous for all data. In this case, it must be assumed that if the same data continues, one of the duplicated data may be unconditionally omitted and omitted. In other words, it is premised that there is no data that may be duplicated in the same format even though the data is of different types.

Taking the above sentence example as an example, an example of data of a pattern in question will be given. The probability of precipitation from 18:00 to 24:00 is 10%, and the expected minimum temperature is 10 degrees. In the above sentence example,% and degrees are not fixed characters in the sentence example, but are included in the data of the fixed form data, so they do not overlap. However, when% and degrees are fixed characters, both data are 10, which is regarded as duplicate data.
As means for avoiding this, it can be determined that the omission is impossible by checking that there is no example in which the minimum expected temperature {8} is omitted in the example data. However, in this case, it is possible to avoid by this method, but it is not always possible to avoid in any case. Therefore, since the data format is the same even for different types of data, there is a possibility that it is erroneously determined that they are duplicates. It is necessary to create fixed-form data and sentence examples so as not to make certain data arrangements and sentence examples.

As another method of determining data to be subjected to duplication check, there is a method of designating data to be subjected to duplication check. As a specific specification method, a method of providing a duplication check flag for each data in the standard data, a method of providing a separate file for a duplication check instruction, or a method of storing the duplication check data as a parameter of the program of the sentence example storage unit 1 are described. There is a way to specify. As described above, the check includes the duplication check of data in one fixed data and the duplication check of data in a plurality of fixed data. The check in one fixed data includes a plurality of data groups to be checked. there's a possibility that. for that reason,
Data must be flagged so that they can be distinguished.

As an example in which a flag is set for each data of the regular data, in the above-mentioned sentence example,% of the precipitation probability and the degree of the expected temperature are used as fixed characters in the sentence example. Here is an example that makes it impossible to distinguish between and the expected temperature. FIG. 7A shows an example in which a flag is set for each piece of regular data. The flag "*" in front of the district name indicates that if data overlaps over a plurality of regular data, it is omitted from the second time onward.
The data of the precipitation probabilities 1 to 4 and the expected minimum temperature / expected maximum temperature are numerical values, and it cannot be determined unless the data is instructed.
The flag of all the precipitation probabilities 1 to 4 is set to 1 and 1
It shows the same group of data that can be omitted in one regular data. If there are a plurality of groups that can be omitted in one regular data, different numbers or characters may be set for each group. The blank portion of the flag is data that cannot be omitted.

When each data in the standard data is not provided with a duplication flag and the instruction of the data to be duplication checked is stored in another file or is indicated by a parameter, "* ,,, 1,1" A duplication check instruction such as "1,1,1 ,," is input to specify what duplication check item is required.

As described above, when the data to be subjected to the duplication check is designated, it becomes clear which data and what duplication check should be performed for which data, and the duplication check can be executed without mistake.

When the duplication check is completed and which data is to be omitted is determined, it is necessary to select a corresponding sentence example. The sentence example to be selected is determined by which data is omitted, but the target sentence example is not limited to one. In this case, a sentence example to be used is determined from the target sentence example by the selection method used in the first embodiment. A method of identifying the target sentence example after the data to be omitted is determined will be described below.

First, a first method of identifying the target sentence example is a method of reading all the sentence examples each time the fixed form data is read, and identifying all the sentence examples not including the data name to be omitted in the sentence examples. This is the simplest method, but the most inefficient method, because every sentence example is checked and the target sentence example is identified each time the standard data is read. However, if all the sentence examples are checked only once at the first time, and the sentence example and a table indicating which data is omitted from the sentence example are created, the sentence example can be referred to from the second time onward by referring to this table. It is not necessary to repeatedly determine which data is omitted, and since the sentence example itself has already been stored in the table, there is no need to read it again from the sentence example storage unit 1-2, so that efficient processing can be performed. become.

Next, a second method for identifying the target sentence example is to store a sentence example with an index indicating what data is omitted in the sentence example, and when the data to be omitted is found from the fixed form data, This is a method of creating an index by omitting which data and searching for the target sentence example by that. An example is given below.

For example, when the first data and the sixth data are omitted, a method of obtaining an index is determined in advance so that an index of 16 is obtained. Since there may be a plurality of target sentence examples, the sentence example is an indexed file having a duplicate key. Since there is a sentence example with a duplicate key, the value of 16 is first positioned as the first sentence example of the target sentence example of the file containing the sentence example, and the reading is sequentially performed from there until the index is no longer the value of 16. Then, identify all the target sentences. The index may be a non-abbreviated sentence example number, an abbreviated data name, or the like, instead of the abbreviated data number, but the abbreviated data number is more preferable as the index because the index is shorter.

When the duplication check is performed only in one fixed data, the processing is performed by reading the fixed data one by one. Therefore, the flowchart is the same as that of FIG. 2, but the duplication of the data over a plurality of fixed data is performed. Is checked, if all the standard data is read at once to make it easier to check, the flow of processing changes, so the flowchart of FIG. 2 changes as follows. First, in order to read all the regular data, it is necessary to read all the fixed data in step S1, store it in the memory, and move to step S3 when the reading of the fixed data is completed. Therefore, as long as the reading of the standard data is not completed in step S2, the process returns from step S2 to step S1, and when the reading of the standard data is completed in step S2, the process proceeds to step S3. From step S4 to step S6, all the read standard data are processed collectively, and when the processing of step S6 ends, the entire processing ends.

As described above, according to the present embodiment, it is possible not only to create a sentence example in which fixed characters are simplified, but also to create a sentence example in which duplicate data is omitted and summarized. It is possible to realize a regular data reading device in which the reading time is further reduced.

[0070]

[Embodiment 4] Next, instead of reading out a sentence in fixed data units, information to be quickly known or important information etc. is read out in a fixed form from the fixed data first. This will be described with reference to FIG. A description of the same parts as those in the first embodiment will be appropriately omitted.

In this embodiment, the fixed form data storage unit 1-
The data of the standard data stored in No. 1 is shown in FIG.
, A flag indicating which data is regarded as a data set is provided. In this example, the fixed form data is 2
This is an example of dividing into two data sets. The first data set is a set of data for which “*” or “#” is designated as a flag, and the other data set is a set of data for which no flag is set. Data for which the flag “*” is set indicates data of a data set to be read out only at the beginning. The data to which the flag “#” is set is one of the data of the data set to be read first, but indicates that the data belongs not only to the first data set but also to another set data. . That is, when the first data set is read out,
When one data set is read out, it indicates that it is common data that is read out.

It is assumed that a sentence example as shown in FIG. 4B is stored in the sentence example storage unit 1-2, and the first three fixed form data in FIG. 7B are read out. The weather on the eastern part on February 1 is fine and cloudy, and on February 2 it is fine.2
On March 3, it is fine and sometimes rainy. Probability of precipitation on February 1, 0% from 0:00 to 6:00, 10% from 6:00 to 12:00, 30% from 12:00 to 18:00, 30 from 18:00 to 24:00
%, The expected minimum temperature will be 0 degrees, the expected maximum temperature will be 10 degrees. Probability of precipitation on February 2, 0% from 0:00 to 6:00, 6%
0% from hour to 12:00, 0% from 12:00 to 18:00
%, 0% from 18:00 to 24:00, the expected minimum temperature is 0
Degree, the expected maximum temperature will be 10 degrees. Probability of precipitation on February 3, 10% from 0:00 to 6:00, 10% from 6:00 to 12:00, 60% from 12:00 to 18:00, 18:00 to 2
By 4 o'clock, the expected minimum temperature will be 0 degrees and the expected maximum temperature will be 10 degrees. ".

In this embodiment, which data of the fixed form data is to be combined is provided by providing a flag for each data. However, this is stored in a separate file, or by using a parameter of the program of the sentence example selection unit 1. May be specified. In the case where the specification of the standard data flag in FIG. 7B is stopped and only the flag is specified by another file or parameter, for example, the specification is performed as “*, #, * ,,,,,” I do. This may be shortened to “*, #, *”.

When the function of the third embodiment is combined with the third embodiment, a flag indicating a set of data and a flag indicating data to be checked for duplication may be overlapped. Need to
The standard data is as shown in FIG. When the first three sentences in FIG. 7C are read aloud by adding a sentence example that collectively expresses the precipitation probability portion of the third sentence example in FIG. 4B, the result is as follows. "The weather on the eastern part of Kanagawa Prefecture on February 1 is cloudy after clearing. On February 2 it is sunny. February 3
The day is sunny and sometimes rainy. Probability of precipitation on February 1, 0% from 0:00 to 6:00, 10% from 6:00 to 12:00, 30% from 12:00 to 24:00, predicted minimum temperature of 0 ° C, predicted maximum temperature of 10% Degree. Probability of precipitation on February 2 from 0:00 to 2
Until 4:00, 0%, the lowest expected temperature is 0 degrees, the highest expected temperature is 10 degrees. The probability of precipitation on February 3 is 10% from 0:00 to 12:00, 60% from 12:00 to 24:00, the expected minimum temperature is 0 degrees and the expected maximum temperature is 10 degrees. In this way, sentences can be further shortened.

According to the present embodiment, it is possible to collectively output data having a high degree of importance in a plurality of fixed data at once and output the subsequent data as detailed data by voice. You will be able to listen only to important information first, and later information will be heard if you do not need it.

As another method, there is a method in which a sentence example has a flag instead of having a flag in fixed data. When this method is used in combination with the specification method of the sentence example of the first embodiment as shown in FIG. 4A, for example, the sentence example shown in FIG. 4C is obtained. First, a flag of 1 is set for a sentence example used for reading out the first data set, and a flag of 2 is set for a sentence example used for reading out the second data set. There are two sentence examples where the flag is 1, and * is specified in the second byte of the second flag so that the first sentence is used only once and the second sentence is used repeatedly. . Then, all the regular data are read out using the sentence example for each flag. By using this method, data can be grouped by checking data used in a sentence example without setting a flag for each data and performing grouping.

In the method of attaching a flag to data or specifying a data set by another file or parameter, data to be used across a plurality of data sets is specified unless the data is essential to all data sets. Although it is difficult to provide several flags, it is difficult to group data by sentence example. Even if you do not specify a data set, the data set is specified by the data used in the sentence example Therefore, the designation method becomes extremely easy.

[0078]

[Embodiment 5] Next, based on standard data and sentence examples,
In addition to reading out data, by creating a table and displaying it on a display device, it is possible to acquire information not only by listening but also by looking at it, used as an in-vehicle information service terminal This will be described with reference to the configuration diagram of FIG. 8 taking car navigation as an example.

In the present embodiment, it is assumed that the fixed data is used as weekly weather forecast data, and that the fixed data and the sentence are transmitted in the form of a text broadcast transmitted by an FM broadcast from a broadcasting station. In addition, a case where road traffic information and weather forecast data for each area are received from a special service station is also included as a part of the so-called ITS system.

The broadcasting station uses the data transmitting section 6 to input the fixed data storage section 6-1 and the sentence example storage section 6-2 in the broadcasting station as input, and broadcast the fixed data and the sentence examples by FM radio waves. In the car navigation, the fixed data and the sentence example are received by the data receiving unit 7 and stored in the fixed data storage unit 7-1 and the sentence example storage unit 7-2 on the car navigation side. The display data creation unit 8 acquires the standard data and the sentence example from the fixed data storage unit 12-1 and the sentence example storage unit 12-2, creates table data, and displays the table data on the display device 15 such as a display. The configuration of the voice data creation unit 9 is such that the fixed form data storage unit 1-1 is provided in the fixed form data storage unit 7-1 and the sentence example storage unit 1-2 is provided in the sentence example storage unit 7- in the configuration diagram of the above-described embodiment.
2 is the same as that of the first embodiment except that the audio output unit 11 is replaced with a sound output device 11 such as a speaker.

The following describes an example of how the display data creation unit 8 creates table data.

When generating the table data, it is assumed that the first sentence example expressing the most polite expression is the input data, and the variables are used not as numbers but as variable names. The standard data is (c) in FIG. 7, and the sentence example is “{district name}”.
The day of the month will be Weather. The probability of precipitation from 0:00 to 6:00 will be {precipitation probability 1%}. From 6:00 1
The chance of precipitation until 2 o'clock will be {precipitation probability 2%}. 12
From 18:00 to 18:00, the probability of precipitation will be {3}%. Precipitation probability from 18:00 to 24:00 is {precipitation probability 4}
%. The expected minimum temperature will be {expected minimum temperature} degrees. The expected maximum temperature will be ≪expected maximum temperature≫ degrees. ".

First, a two-dimensional table having the same format as the table is provided on the memory. At the top of the table, it is necessary to enter an item name to indicate what data, so one line is left at the top of the two-dimensional table in order to enter the item name. Next, a variable name indicating what data is in each column of the table is obtained as an item name from the sentence example. In the case of the above sentence example, the item names are: district name, month, day, weather, precipitation probability 1, precipitation probability 2, precipitation probability 3, precipitation probability 4, predicted minimum temperature, and predicted maximum temperature. All that remains is to read the standard data and store it in the table in order. When a table is created by simply using the variable names as the item names representing the respective data, a weekly weather forecast table as shown in FIG.

Here, in order to make the table easier to read,
Next, add functions. The district name in FIG. 7A is data for performing duplication check over a plurality of standard data, and the first and subsequent district names are omitted. As for the date,
The month and day are disassembled, and if the month is the same, the "~ month" part is omitted.

Next, among the standard data, precipitation probabilities 1 to 4
It can be seen that is data for which duplication check in the standard data is performed, as shown in FIG. That is,
Since the duplication check is data of the same type, if the fixed characters immediately before the variables in the sentence example are checked, the fixed characters immediately before the precipitation probabilities 1 to 4 are “0 to 6”, respectively. The probability of precipitation until time is
"The precipitation probability from 6:00 to 12:00", "12:00 from 12:00"
The probability of precipitation until 8:00 is "and the probability of precipitation from 18:00 to 24:00". Excluding the particle “ha” from each fixed letter, it can be seen that the word consists of the word “precipitation probability” and its modifier. Therefore, it is determined that the “precipitation probability” is a word that summarizes the precipitation probabilities 1 to 4 that are data. For the item name “precipitation probability”, the word “precipitation probability” which is a common part from the precipitation probabilities 1 to 4 which are variable names in the sentence example may be extracted.

[0086] The difference between the precipitation probabilities 1 to 4 is the part that modifies the variable name in the sentence example.
The rainfall probabilities 1-4 are "from 0 o'clock to 6 o'clock", respectively.
"From 6:00 to 12:00", "From 12:00 to 18:00",
"From 18:00 to 24:00"
4 are regarded as distinctive words. Since it is long if it is used as an item name in the table as it is, "from" and "to" are converted to "~", and two-digit numbers are converted to half-width to match the length of each item. The precipitation probabilities 1 to 4 are data to be checked for duplication within one set of data, but are numerical values, and it is not preferable to omit them when putting them into a table. In this case, the area for entering the item name is the upper two rows of the table.

For each data, instead of displaying the regular data as it is, the word immediately after the variable name in the sentence example is checked, and the word immediately after the variable name is converted to a unit such as “%” or “degree”. If it is a word that expresses it, it is included in the table to make the table easier to understand. Regarding the number of digits of each data, check the maximum data length of the corresponding data and the length of the item name, and determine the longer one. Center the item name so that it is in the middle of the number of digits. Numbers are right-justified. As described above, when the item names and the standard data are edited or aligned and tabulated, the table shown in FIG.
A weekly weather forecast table as shown in FIG.

Further, with respect to the expected minimum temperature and the expected maximum temperature, word decomposition is performed, and it is checked whether the ending word of the variable name is the same as the ending word in the variable unit.
If the ending word is the same as the beginning word, it is regarded as a common item,
It can also be extracted as a common item name. For example,
Since the first word "forecast" is the same as the last word "temperature", the expected temperature is taken as a common word, and the item names of each data are "lowest" and "highest", respectively.

As described above, when creating and displaying table data, the table data is displayed with ruled lines. As the ruled line, a format character that is a character representing the ruled line may be used, or a graphic ruled line may be used. When using format characters, secure the area for the format characters on the top, bottom, left and right of each data, and when embedding the appropriate format characters when embedding item names and data in the table, Can be displayed.

According to the present embodiment, when the fixed data can be output not only to the voice but also to the display device, the necessary information can be heard by the voice and can be visually confirmed on the screen. If it can be confirmed visually, the required information can be obtained more quickly. For example, in the case of car navigation, it is dangerous to watch the screen while driving a car, so it is dangerous to listen to the voice, and when stopping at a signal etc., look at the screen so that information can be acquired faster than listening by ear. Become.

[0091]

[Embodiment 6] Next, an embodiment in which a sentence including a table is input and the fixed form data represented in the table is read out will be described with reference to FIG.

Regarding a device for reading out a data portion of a table in a sentence by voice, a document reading device (Japanese Patent Laid-Open No.
-46607) ". In the document reading device, a ruled line is converted to a ruled line fragment (corresponding to a format character).
Check the table to detect the table, calculate the data position on the table from the ruled line information, extract the item names and data, and, if necessary, interact with the user to specify the table reading information. Can read only information. As for the reading method, assuming that the item name is the brand and the data is the company A, it is simply read as “brand, company A”.

In the present embodiment, the function of the sentence / table discriminating section 12 for discriminating a table portion is to detect a format-format character to discriminate a table. Since it is the same as the classification function, detailed description is omitted.
The table structure analysis unit 13 analyzes from what byte to how many bytes each data is in the table, and extracts an item name and data. Up to this point, the functions are the same as those of the above-described document reading device.
In the document reading apparatus, for example, if there is a table as shown in FIG. 9A, "area name, eastern Kanagawa prefecture. Mon., Feb. 1. Weather, cloudy after clearing, precipitation probability 1, 0. Precipitation probability 2, 10. Precipitation probability 3, 30. Precipitation probability 4, 30. Expected low temperature, 0. Expected high temperature, 10. District name, eastern Kanagawa prefecture.Monday, February 2, weather, sunny.- ... ”. In the document reading aloud device, by specifying table reading information, the probability of precipitation is reduced to 1 to 4%.
It is possible to add a guess, set the expected minimum and maximum temperatures, and read only the necessary information. However, it is not possible to check the duplication of data and change the reading method. In addition, as shown in FIG. 9B, when the column of the item name extends over a plurality of lines, when there is a large item that summarizes detailed items, or when the table is made easier to read, such as a district name or a month and day. Therefore, if the data is omitted, it cannot be handled.

In the present embodiment, the table structure analysis unit 13
Further, a function for retrieving a table item name as shown in FIG. 9B, a function for compensating for a portion where data is omitted, a method of duplication check and an item to be duplicity checked from a table writing method, and In addition, it has a function to create standard data and sentence examples.

First, the item names are fetched. If there is a table as shown in FIG. 9B, in the topmost column of the table,
Check the column with the largest number of rows. Here, since the district name, month, day, and weather are spread over three lines, the top three rows are regarded as item names. With regard to the district name, month, day, expected weather minimum temperature, and expected maximum temperature, the data for the three lines in the column is extracted as one continuous data, and blanks are left-justified, so that the "area name" becomes the item name. "·"time"·
Extract "weather", "weather expected minimum temperature", "expected maximum temperature". Although there is a space between the item names "weather", this becomes a problem when converting to the intermediate notation, so it should be padded.

As for the column of “precipitation probability”, since “precipitation probability” is one column and four columns are provided below the column, “precipitation probability” is a word that summarizes the following four items. It is determined that the four items are the same type of data and that the duplicate check can be performed. As a result, it is possible to create a sentence example in which the duplication check is put together, and to generate standard data with the duplication check flag set. Regarding the four item names representing the probability of precipitation, when creating a sentence example, “〜” is converted to “kara” to generate fixed characters of the sentence example.

Next, looking at the standard data, regarding the data of the district name, when the data is checked, since the second and subsequent cases are omitted, it is considered that the duplication check that the district name straddles the standard data is possible. I can do it. As for the date data, February of the second and subsequent data is omitted. However, since items such as date are generally often used, they are omitted inside the table structure analysis unit 13. "2
It is desirable to incorporate a process for restoring the month for general use.

Further, the units such as the probability of precipitation and the percentage and degree of the expected temperature may be set as outside sentences as sentence examples in order to reduce the data amount of the standard data. When the data is restored / generated and the duplication flag is set in this way, the table of FIG. 9B can be converted into the data of FIG. 7A.

In this way, when a sentence example is created based on the extracted item names and the extracted units and supplementing the minimum particles, etc., the expression “district name is {district name}. {Monday} .The weather is {Weather} .Precipitation probability, from 0:00 to 6:00,
From 0:00 to 6: 00%, from 6:00 to 12:00, from 6:00 to 12:00
%, From 12:00 to 18:00, {12:00 to 18:00}%, 18
From 18:00 to 24:00, the rate is from 18:00 to 24:00. The expected minimum temperature is {expected minimum temperature} degrees. The expected maximum temperature is {expected maximum temperature} degrees. "Is the most basic sentence example, and 16 kinds of sentence examples can be created by summarizing the precipitation probabilities and omitting the district names.

The subsequent steps are the same as those in the first embodiment except that the sentence portion in the document is passed from the document / table discriminating section 12 to the sentence analyzing section 3, and therefore the description is omitted. .

According to the present embodiment, a table part existing in a document can be read out by generating a sentence example or fixed form data from the table and converting the table data into various sentences. Without having to listen to the information in the table, it is also possible to listen to the information in a shorter form.

Next, a recording medium in which a program for realizing the data reading apparatus according to the first to sixth embodiments of the present invention is described, as shown in the example of the recording medium shown in FIG.
Not only the portable recording medium 15 such as the ROM 15-1 and the floppy disk 15-2, but also any other storage device 14 stored at the end of a communication line, or the recording medium 17 such as a hard disk or a RAM of a computer. The data is read by the computer 16 when using the fixed form data reading device according to the present invention.

[0103]

According to the data reading device of the present invention,
When reading fixed form data expressed in a table, etc., instead of reading out sentences in the same format repeatedly, read out different sentences for each fixed form data, collectively read out duplicate data, and read only necessary information Therefore, the listener can hear necessary information in a short time without getting bored. Therefore, it is extremely effective to provide voice information to a user by applying the present invention to an in-vehicle information service terminal device or the like.

[Brief description of the drawings]

FIG. 1 is a basic configuration diagram of the present invention.

FIG. 2 is a flowchart showing a basic processing flow of the present invention.

FIG. 3 is a configuration diagram of a data reading device according to the first embodiment of the present invention;

Fig. 4 Data contents of sentence example

FIG. 5 is a configuration diagram of a data reading device according to a second embodiment of the present invention;

FIG. 6 is a flowchart showing a processing flow according to the second embodiment of the present invention;

Fig. 7 Example of fixed data

FIG. 8 is a configuration diagram of a data reading device according to a fifth embodiment of the present invention;

[Figure 9] Weekly weather forecast table

FIG. 10 is a configuration diagram of a data reading device according to a fifth embodiment of the present invention;

FIG. 11 is an exemplary diagram of a storage medium.

[Explanation of symbols]

1 sentence example selection unit 1-1 fixed data storage unit 1-2 sentence example storage unit 2 sentence synthesis unit 3 sentence analysis unit 3-1 morphological dictionary 4 speech synthesis unit 4-1 speech unit dictionary 5 fixed data conversion unit 5-1 fixed format Data morphological dictionary 6 Data transmission unit 6-1 Broadcast station-side fixed data storage unit 6-2 Broadcast station-side sentence example storage unit 7 Data receiving unit 7-1 Car navigation-side fixed data storage unit 7-2 Car navigation side Sentence example storage unit 8 display data creation unit 9 audio data creation unit 10 display device such as display 11 audio output device such as speaker 12 text / table discrimination unit 12-1 text storage unit 13 table structure analysis unit 14 ahead of communication line Other stored storage device 15 Portable storage media such as CD-ROM and floppy disk 15-1 CD-ROM 15-2 Floppy disk 16 Computer Data 17 Storage media such as RAM / hard disk on computer

Claims (7)

[Claims] 1. A data reading device for synthesizing a sentence based on fixed data having a specific format composed of one or more data and outputting a voice, a sentence example storage unit for storing a plurality of sentence examples for embedding the fixed data. A data reading device comprising: a sentence synthesizing unit that reads the fixed form data and synthesizes a sentence by changing a sentence example to be embedded for each fixed form data. 2. A data reading device for synthesizing a sentence based on fixed data having a specific format composed of one or more data and outputting a speech, a fixed data storage unit for storing a plurality of the fixed data, the fixed data A sentence example storage unit that stores a plurality of sentence examples for embedding, from the sentence example storage unit, a sentence example selection unit that selects different sentence examples to be embedded for each of the fixed form data, based on the fixed form data and the selected sentence example, A text synthesizing unit for synthesizing a document, a text analyzing unit for analyzing the synthesized document and converting it to an intermediate notation for expressing speech, and a speech synthesis for synthesizing and outputting speech based on the intermediate notation. A data reading device comprising a unit. 3. A data reading device for synthesizing a sentence based on fixed data having a specific format composed of at least one data and outputting the synthesized sound, a fixed data storage unit for storing a plurality of the fixed data, the fixed data A sentence example storage unit that stores a plurality of sentence examples in the form of intermediate notation for expressing speech, a sentence example selection unit that selects different sentence examples to be embedded for each of the standard data from the sentence example storage unit, A fixed form data conversion unit for converting the fixed form data into intermediate notation; a sentence synthesis unit for synthesizing a document based on the converted fixed form data and the selected sentence example; and a speech synthesis unit for synthesizing the speech based on the synthesized sentence. A data reading device comprising a voice synthesizing unit for outputting. 4. Each of the standard data includes a duplication check flag indicating whether or not a duplication check is to be performed. The sentence example storage unit stores a sentence example that collectively expresses an overlapping portion of the fixed data, The sentence example selecting unit, based on the duplication check flag,
4. The data reading apparatus according to claim 2, further comprising a function of inspecting an overlapped portion of the fixed data and selecting a sentence example that summarizes the corresponding overlapped portion. 5. A sentence example in which each data of the fixed form data includes a data set flag indicating a set of data to be read aloud in the fixed form data, wherein the sentence example storage unit includes only data of the data set in a data set unit. The pre-sentence example selection unit has a function of reading all the fixed form data collectively and selecting a corresponding sentence example in a specified data set unit. A data reading device according to any one of the above. 6. A computer-readable recording medium having recorded thereon a program for causing a computer to execute a step of synthesizing a sentence based on fixed data having a specific format composed of one or more data and a step of outputting the sentence as sound. Recording a program that causes a computer to execute: a step of storing a plurality of sentence examples for embedding the fixed form data; and a step of reading the fixed form data and synthesizing a sentence by changing a sentence example to be embedded for each of the fixed form data. Computer readable recording medium. 7. A computer-readable recording medium on which a program for causing a computer to execute a step of synthesizing a sentence based on fixed data having a specific format including one or more data and a step of outputting the sentence as sound is recorded. A step of storing a plurality of the fixed form data; a step of storing a plurality of sentence examples for embedding the fixed form data; and a step of selecting a different sentence example to be embedded for each of the fixed form data from the stored sentence examples. Synthesizing a document based on the fixed form data and the selected sentence example; analyzing the synthesized document to convert it into an intermediate notation for expressing speech; and And outputting the synthesized speech based on the program. Data-readable recording medium.