JP2020160118A - Information processing device, information processing method and program - Google Patents

Abstract

To suitably generate a dictionary for voice recognition.SOLUTION: A first voice recognition result based on a first dictionary and a second voice recognition result based on a second dictionary are received, and a first confidence level about the first voice recognition result calculated based on predetermined operation, and a second confidence level about the second voice recognition result calculated based on the operation are received. The first confidence level and the second confidence level are compared with each other, and if a predetermined condition is satisfied, word information contained in the second voice recognition result is registered. The second dictionary includes the word information registered in the first dictionary, and the word information designated by a user.SELECTED DRAWING: Figure 5

Description

The present invention relates to information processing devices, information processing methods and programs.

In the voice recognition device for unspecified persons, a dictionary for voice recognition centering on general-purpose and general vocabulary is registered in advance, and the voice recognition device is a registered dictionary for voice recognition. Recognize voice based on. In such a speech recognition device, if the vocabulary to be recognized can be defined at the time of design, a pre-created speech recognition dictionary is used, but if the vocabulary cannot be defined, or it should be changed dynamically. In some cases, human input is generally performed, or a vocabulary for speech recognition is automatically generated from character string information and registered in a dictionary.

Further, in recent voice recognition devices, for example, by registering paraphrase expressions such as abbreviations in a dictionary for voice recognition, not only formal word utterances but also arbitrary abbreviations by users can be dealt with. are doing.

For example, Patent Document 1 discloses a speech recognition device capable of recognizing abbreviated paraphrase expressions of words with a high recognition rate.

Japanese Patent No. 3724649

However, in the speech recognition device disclosed in Patent Document 1, new words (special) that are general and uncommon, such as company-specific internal terms and special terms that appear at this conference or lecture, are used. When registering a term) in a speech recognition dictionary, it is necessary to input by human work, and the burden of human work such as selection and input of words to be registered is heavy. Therefore, it is still insufficient from the viewpoint of suitably generating a dictionary for speech recognition.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an information processing device, an information processing method, and a program capable of suitably generating a dictionary for voice recognition.

In order to achieve the above object, the information processing device according to the first aspect of the present invention is
A voice recognition result receiving means for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence receiving means and
A word information registration means for registering word information included in the second voice recognition result when the first certainty degree and the second certainty degree are compared and a predetermined condition is satisfied is provided.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
It is characterized by that.

When the predetermined conditions are satisfied, an extraction means for extracting word information to be registered from the second voice recognition result according to a predetermined standard is further provided.
The word information registration means registers the word information extracted by the extraction means.
You may do so.

Further provided with a classification means for classifying the word information extracted by the extraction means into one of a plurality of predetermined classifications for each occurrence frequency.
The word information registration means registers word information classified by the classification means for each classification.
You may do so.

The word information includes voice information and character information.
A first dictionary update means for updating the first dictionary by adding the word information registered by the word information registration means to the first dictionary is further provided.
The second dictionary is newly stored by the operation of the user every time the first dictionary is updated.
You may do so.

In order to achieve the above object, the information processing method according to the second aspect of the present invention is
A voice recognition result receiving step for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence reception step and
A word information registration step of comparing the first certainty degree and the second certainty degree and registering the word information included in the second voice recognition result when a predetermined condition is satisfied is provided.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
It is characterized by that.

In order to achieve the above object, the program according to the third aspect of the present invention is
Computer,
A voice recognition result receiving means for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence receiving means,
When the first certainty degree and the second certainty degree are compared and a predetermined condition is satisfied, the word information included in the second voice recognition result is registered as a word information registration means.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
It is characterized by that.

According to the present invention, a dictionary for voice recognition can be preferably generated.

It is a block diagram which shows an example of the information processing system which concerns on embodiment of this invention. It is a block diagram which shows an example of the information processing apparatus which concerns on embodiment of this invention. It is a block diagram which shows an example of the voice recognition server which concerns on embodiment of this invention. It is explanatory drawing for demonstrating the overall processing of an information processing system. It is a flowchart which shows an example of a term registration process. It is a figure which shows an example of the voice recognition result. It is a figure which shows an example of a morpheme and a part of speech of a speech recognition result.

An example in which the information processing device 100 in the present invention is applied to the information processing system 1 shown in FIG. 1 will be described. In the information processing system 1, as shown in FIG. 1, the information processing devices 100A and 100B and the voice recognition server 200 are communicably connected via the network 510. In order to facilitate understanding, in this embodiment, a case where the user of the information processing device 100A and the user of the information processing device 100B have a conversation with each other will be described below as an example. The information processing device 100A and the information processing device 100B are also simply referred to as an information processing device 100.

The information processing device 100 is an information terminal (so-called computer) such as a mobile phone, a smartphone, a tablet, or a PC (Personal Computer), and constructs a distributed network 510 such as P2P (Peer to Peer). The information processing system 1 is not limited to the P2P type system, and may be, for example, a cloud computing type.

The information processing device 100 has a function of outputting voice data and text data (voice recognition result) of conversations of other users of the information processing device 100 received from the voice recognition server 200. Further, the information processing device 100 has a function of extracting word information to be registered from the voice recognition result based on the certainty level received from the voice recognition server 200 and registering the word information in the voice recognition dictionary.

The voice recognition server 200 is, for example, a mainframe, a workstation, or an arbitrary computer device such as a PC (Personal Computer). The voice recognition server 200 recognizes the voice (contents of the conversation) transmitted from the information processing device 100 based on the pre-stored dictionary for voice recognition, and the recognized voice data together with the text data (as a voice recognition result). ) It has a function of transmitting to another information processing device 100. The voice recognition server 200 also has a function of calculating a certainty degree indicating the probability that the vocabulary obtained as a voice recognition result matches the actually spoken vocabulary and transmitting it to another information processing device 100. There is.

Next, the configuration of the information processing device 100 (information processing device 100A and information processing device 100B shown in FIG. 1) in this embodiment will be described with reference to FIG. Although not shown, it is assumed that a functional unit having a function of converting a user's conversation (voice) as voice data for transmission (from analog to digital) (and vice versa) is provided. To do.

As shown in FIG. 2, the information processing apparatus 100 includes a storage unit 110, a control unit 120, an input / output unit 130, a communication unit 140, and a system bus (not shown) that connects them to each other. ing.

The storage unit 110 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. The ROM stores a program executed by the CPU (Central Processing Unit) of the control unit 120 and data necessary for executing the program in advance (not shown).

Specifically, the storage unit 110 in this embodiment stores voice data of words to be registered as a dictionary for voice recognition and text data thereof as a registered term list 111. The voice data and the text data corresponding to the voice data are also collectively referred to as word information. The registered term list 111 shows a list of word information to be registered, and includes a plurality of word information. The word information of the registered term list 111 is stored in the storage unit 110 for each classification by the term registration process described later. Further, the storage unit 110 stores a list of registered classifications classified based on the user's designation as the registration classification 112 and the classification criteria thereof. As the registration classification, for example, a classification such as "universally used in-house term" and a classification such as "internal term used in a specific organization" are registered based on the designation by the user. As a classification standard, for example, the frequency of appearance of the word information to be registered during conversation is memorized, and the word information that appears 5 times or more is classified as "universally used in-house term". If it is less than 5 times, it may be arbitrarily set by the user, such as classifying it into "internal terms used in a specific organization".

The control unit 120 is composed of a CPU, an ASIC (Application Specific Integrated Circuit), and the like. The control unit 120 operates according to the program stored in the storage unit 110, and executes the process according to the program. The control unit 120 includes a certainty comparison unit 121, a morpheme extraction unit 122, a part of speech estimation unit 123, a term classification unit 124, and term registration as main functional units provided by a program stored in the storage unit 110. A unit 125 is provided.

The certainty comparison unit 121 is a functional unit that compares the certainty transmitted from the voice recognition server 200. Although details will be described later, the voice recognition server 200 is based on the voice recognition result (based on the first registered term list 211 described later) when the first registered term list 211 is used as a speech recognition dictionary (first dictionary). Voice recognition result (described later) when text data and its voice data), its certainty A (first certainty), and the second registered term list 212 are used as a voice recognition dictionary (second dictionary). 2 Text data based on the registered term list 212 and its voice data) and its certainty B (second certainty) are transmitted. The certainty comparison unit 121 compares the certainty A with the certainty B. Specifically, the certainty comparison unit 121 compares the certainty by determining whether or not the value obtained by subtracting the certainty A from the certainty B is equal to or higher than a predetermined threshold value. The threshold value may be set by the user, for example, depending on the content of the conference, the language used, and the like.

The morphological element extraction unit 122 uses, for example, the voice recognition result (first voice recognition result) when the first registered term list 211 is used as a speech recognition dictionary and the second registered term list 212 as a speech recognition dictionary. It is a functional unit that extracts different morphemes by dividing each of the voice recognition result (second voice recognition result) when used into each morpheme by morphological analysis or the like. Specifically, the morpheme extraction unit 122 extracts different morphemes by subtracting the morpheme of the intersection with the first speech recognition result divided for each morpheme from the second speech recognition result divided for each morpheme.

The part of speech estimation unit 123 is a functional unit that extracts morphemes of different part of speech by comparing the part of speech of each morpheme of the first speech recognition result and the second speech recognition result. Specifically, the part-speech estimation unit 123 compares the morpheme of the first speech recognition result with the morpheme of the second speech recognition result, and although the part of speech of the morpheme of the second speech recognition result is a noun, the first speech recognition result Extract morphemes whose morphemes are other than nouns. That is, the morpheme extraction unit 122 extracts the morpheme (different character string) of a word different from the first speech recognition result from the second speech recognition result, whereas the part of speech estimation unit 123 extracts the morpheme (different character string) of the word from the second speech recognition result. Extract morphemes of part of speech that differ from the first speech recognition result. In other words, it can be said that the morpheme extraction unit 122 is a functional unit that extracts morphemes from the viewpoint of a character string, and the part of speech estimation unit 123 is a functional unit that extracts morphemes from the viewpoint of part of speech. Special terms such as "universally used internal terms" and "internal terms used within a specific organization" are often nouns. Therefore, the part of speech estimation unit 123 in this embodiment extracts a morpheme whose morpheme of the second speech recognition result is a noun but whose morpheme of the first speech recognition result is other than a noun. Unlike this, the morphemes of different part of speech may be simply output to the input / output unit 130, and the user may select whether or not to extract them.

The term classification unit 124 determines whether or not the morpheme extracted by the function of the morpheme extraction unit 122 and the morpheme extracted by the function of the part of speech estimation unit 123 match, and if they match, the term classification unit 124 recognizes the morpheme as a registration target. , Is a functional unit that classifies the word information of the certified morpheme to be registered based on the classification based on the registration classification 112. Specifically, when the extracted morphemes match, the term classification unit 124 is registered according to the classification criteria set as the registration classification 112 based on the appearance frequency of the word information to be registered. It is classified into the above classification.

The term registration unit 125 is a functional unit that registers the word information classified by the term classification unit 124 in the registered term list 111 for each classification. Further, the term registration unit 125 also has a function of transmitting an update instruction for updating the contents of the first registered term list 211 to the voice recognition server 200 based on the contents of the word information registered in the registered term list 111. There is. The term registration unit 125 is a function as a word information registration means.

Each of these functional units cooperates to realize a function of registering word information to be registered in a speech recognition dictionary in the information processing device 100.

The input / output unit 130 is composed of a keyboard, a mouse, a camera, a microphone, a liquid crystal display, an organic EL (Electro-luminescence) display, and the like, and is a device for inputting / outputting data.

The communication unit 140 is a device for communicating with another information processing device 100 or a voice recognition server 200 via a network 510.

The above is the configuration of the information processing device 100. Next, the configuration of the voice recognition server 200 in this embodiment will be described with reference to FIG. As shown in FIG. 3, the voice recognition server 200 includes a storage unit 210, a control unit 220, an input / output unit 230, a communication unit 240, and a system bus (not shown) that connects them to each other. ing.

The storage unit 210 includes a ROM, a RAM, and the like. The ROM stores a program executed by the CPU of the control unit 220 and data necessary for executing the program in advance (not shown).

Specifically, the storage unit 210 in this embodiment stores the first registered term list 211 and the second registered term list 212 as a dictionary for voice recognition. The first registered term list 211 is a list of word information, and the registered word information is updated every time the term registration process described later is executed. The initial first registered term list 211 may be a list of word information centered on a general-purpose and general vocabulary, and may be generated by a user or is open to the public on the network, for example. You may get it by downloading the one.

On the other hand, the second registered term list 212 has more special term words such as "universally used in-house term" and "internal term used in a specific organization" than the first registered term list 211. It is a list of word information generated by the user so as to include a lot of information. The second registered term list 212 may be generated by the user for each meeting or lecture, for example, based on the material of the scheduled meeting or the material of the lecture. In the information processing apparatus 100 according to this embodiment, for example, the second registered term list 212 is newly stored for each meeting (in other words, every time the first registered term list 211 is updated), and the term registration process described later is performed. Will be done. In the term registration process, the target word information is registered by comparing the second registered term list 212 with the first registered term list 211. Therefore, special terms such as "universally used in-house terms" can be suitably registered in the speech recognition dictionary, and the speech recognition dictionary can be updated by repeatedly executing the terms. It becomes.

The control unit 220 is composed of a CPU, an ASIC, and the like. The control unit 120 operates according to the program stored in the storage unit 110, and executes the process according to the program. The control unit 220 includes a voice recognition processing unit 221 and a certainty calculation unit 222 as main functional units provided by the program stored in the storage unit 210.

The voice recognition processing unit 221 has a function of converting, for example, voice data received from the information processing device 100 into text data based on the first registered term list 211 and text data based on the second registered term list 212. It is a department. The conversion from voice data to text data may be performed by a conventionally used voice recognition technique based on the first registered term list 211 and the second registered term list 212. The voice recognition processing unit 221 also has a function of transmitting each converted text data together with the voice data to another information processing device 100.

The certainty calculation unit 222 is a functional unit that calculates the certainty corresponding to the text data converted by the voice recognition processing unit 221. Specifically, the certainty calculation unit 222 calculates the certainty A of the text data based on the first registered term list 211 and the certainty B of the text data based on the second registered term list 212, respectively. The degree of certainty is, for example, the similarity between the voice features (waveform, period, etc.) of the word information registered in the first registered term list 211 and the second registered term list 212 and the voice features based on the received voice data. It may be calculated based on (calculated based on a predetermined calculation). The certainty calculation unit 222 also has a function of transmitting each calculated certainty to another information processing device 100.

These functional units work together to convert the voice data received from the information processing device 100 into text data (speech recognition) in the voice recognition server 200, and perform other information processing as a voice recognition result together with the voice data. The function of transmitting to the device 100 is realized. Moreover, the function of transmitting the certainty degree to another information processing apparatus 100 is realized.

The input / output unit 230 is composed of a keyboard, a mouse, a camera, a microphone, a liquid crystal display, an organic EL display, and the like, and is a device for inputting / outputting data.

The communication unit 240 is a device for communicating with the information processing device 100 via the network 510.

The above is the configuration of the voice recognition server 200. Subsequently, the operation of the information processing apparatus 100 and the like will be described with reference to FIGS. 4 to 7. First, as the operation of the information processing system 1, the overall processing flow will be described with reference to FIG. In the illustrated example, the case where the user of the information processing device 100B speaks the content of the example sentence 1 to the user of the information processing device 100A will be described below as an example.

As shown in FIG. 4, when the user of the information processing apparatus 100B inputs the voice of the example sentence 1 to the input / output unit 130, the voice data is converted into voice data by the function of the control unit 120, and the voice data is transmitted to the voice recognition server 200. ((1) in FIG. 4). In the illustrated example, the voice data is transmitted from the information processing device 100B to the voice recognition server 200 in order to facilitate understanding. For example, the information processing device 100B to the information processing device 100A. And the specific voice data extracted by the information processing apparatus 100A may be transmitted to the voice recognition server 200.

When the voice recognition server 200 receives the voice data from the information processing device 100B, the voice recognition processing unit 221 functions to perform voice recognition (converted to text data) based on the first registered term list 211, and the voice data is combined with the voice data. The text data is transmitted to the information processing device 100A as the first voice recognition result ((2) in FIG. 4). Further, the voice recognition server 200 calculates the certainty level A of voice recognition based on the first registered term list 211 by the function of the certainty degree calculation unit 222, and transmits it to the information processing device 100A ((3) in FIG. 4). ..

Further, the voice recognition server 200 performs voice recognition (converts to text data) based on the second registered term list 212 by the function of the voice recognition processing unit 221 and converts the voice data and the text data into the second voice recognition result. Is transmitted to the information processing device 100A ((4) in FIG. 4). Further, the voice recognition server 200 calculates the certainty level B of voice recognition based on the second registered term list 212 by the function of the certainty degree calculation unit 222, and transmits it to the information processing device 100A ((5) in FIG. 4). .. In addition, (2) to (5) of FIG. 4 may be performed collectively.

On the information processing device 100A side, the voice data and the text data based on the second registered term list 212 received from the voice recognition server 200 are output from the input / output unit 130 (the contents shown in FIG. 6B are output). ). Further, when the information processing apparatus 100A receives the first voice recognition result and the second voice recognition result (including the certainty degree A and the certainty degree B) from the voice recognition server 200 (in the voice recognition result receiving means and the certainty degree receiving means). (Equivalent), perform the term registration process for registering the special term to be registered in the dictionary for voice recognition. That is, the information processing device 100A performs a process for registering the special term included in the user's remark of the information processing device 100B in the dictionary for voice recognition. In the following, the voice data and text data of the content shown in FIG. 6 (A) are received as the first voice recognition result, and the voice data and text data of the content shown in FIG. 6 (B) are used as the second voice recognition result. A case where the data is received and the second voice recognition result "NTT" is registered as a special term will be described (the confidence level is also a value shown in the figure).

FIG. 5 is a flowchart showing an example of the term registration process. In the term registration process, the information processing apparatus 100A uses the function of the certainty comparison unit 121 to determine whether or not the value obtained by subtracting the certainty A from the certainty B is equal to or higher than a predetermined threshold value (predetermined condition). Whether or not the condition is satisfied) is determined (step S101). If it is less than the threshold value, the information processing apparatus 100A terminates the term registration process as it is, assuming that there is no target to be registered. Specifically, in the process of step S101, the certainty degree 0.16 shown in FIG. 6 (A) is subtracted from the certainty degree 0.89 shown in FIG. 6 (B) to determine whether or not it is equal to or greater than the threshold value. It is assumed that the threshold value in this example is set to 0.5 in advance by the user.

When the value is equal to or higher than the threshold value (step S101; Yes), the information processing apparatus 100A uses the function of the morpheme extraction unit 122 to set each of the first voice recognition result and the second voice recognition result received from the voice recognition server 200 for each morpheme. It is divided and different morphemes are extracted from the second speech recognition result (step S102). In step S102, the text data in the first voice recognition result may be divided into morphemes, different morphemes may be extracted, and then the voice data of the portion corresponding to the morpheme may be extracted. Further, both the text data and the voice data in the first voice recognition result may be divided into morphemes, and different morphemes may be extracted for each. Specifically, in step S102, since the morphemes of "Venditti" shown in FIGS. 6 (A) and 7 (A) and "NTT" shown in FIGS. 6 (B) and 7 (B) are different, FIG. 6 ( The morpheme of "NTT" shown in B) and FIG. 7 (B) is extracted. It should be noted that "Venditti" shown in FIGS. 6 (A) and 7 (A) is a coined word used for facilitating understanding in this embodiment, and it is assumed that the part of speech is an adjective. Further, in the following, it is assumed that the frequency of appearance of the "NTT" is 5 times, and the frequency of appearance of the "NTT" is 6 times in this example sentence 1.

After executing the process of step S102, the information processing apparatus 100A compares the morpheme of the first speech recognition result with the morpheme of the second speech recognition result by the function of the part of speech estimation unit 123, and the morpheme of the second speech recognition result. A morpheme whose part of speech is a noun but whose morpheme of the first speech recognition result is other than a noun is extracted (step S103). As described above, in step S103, the morphemes of different part of speech may be simply output to the input / output unit 130, and the user may select whether or not to extract them. Specifically, in the process of step S103, the part of speech of "Venditti" shown in FIG. 7 (A) is an "adjective", and the part of speech of "NTT" shown in FIG. 7 (B) is a "noun". The morpheme of "NTT" shown in FIG. 7B is extracted. Further, in this embodiment, as shown in FIG. 7, a preposition such as "of" is excluded from comparison because it is an unnecessary part of speech from the viewpoint of registration in a dictionary for speech recognition.

After executing the process of step S103, the information processing apparatus 100A determines whether or not the morpheme extracted in step S102 and the morpheme extracted in step S103 match by the function of the term classification unit 124 (step S104). .. If they do not match (step S104; No), the term registration process ends. If they do not match, the user is asked to select whether or not to register the word information corresponding to each of the morpheme extracted in step S102 and the morpheme extracted in step S103 in the registered term list 111, and neither is registered. In this case, when the term registration process is terminated and at least one of them is registered, the process may proceed to step S105. In this embodiment, it is determined whether or not the morphemes extracted in the process of step S102 and the process of step S103 match, but only the process of step S102 or only the process of step S103 is performed, and the process of step S105 is performed. You may move to processing. Further, if the processes of steps S102 to S104 are not executed and a Yes is determined in step S101, the process may shift to the process of step S105. In this case, for example, the certainty of each morpheme may be transmitted from the voice recognition server 200.

When it is determined that they match (step S104; Yes), the information processing apparatus 100A certifies the word information corresponding to the extracted morpheme as the registration target by the function of the term classification unit 124, and the certified morpheme of the registration target. The word information of is classified based on the classification based on the registration classification 112 (step S105). Specifically, in the process of step S105, since the frequency of appearance of the word information of "NTT" is 6, the "NTT" is classified into the "universally used in-house term". The "universally used in-house term" includes, for example, a term commonly used in a plurality of projects.

After executing the process of step S105, the information processing apparatus 100A uses the function of the term registration unit 125 to collect voice data and text data as word information classified by the process of step S104 in the registered term list 111 according to the classification. Register in (step S106). Specifically, in the process of step S106, the voice data and the text data of "NTT" classified into the classification of "universally used in-house terms" are associated with each other, and the "universal" in the registered term list 111 is used. Register as a classification of "in-house terms used in".

After executing the process of step S106, the information processing apparatus 100A updates the content of the first registered term list 211 based on the content of the word information registered in the registered term list 111 by the function of the term registration unit 125. The update instruction is transmitted to the voice recognition server 200 (step S107), and the term registration process is completed. Specifically, in the process of step S107, the voice data and text data of "NTT" registered as the classification of "universally used in-house terms" in the registered term list 111 are transmitted to the voice recognition server 200 together with the update instruction. Then, the voice data and the text data of the "NTT" are additionally registered in the first registered term list 211 stored in the voice recognition server 200. As a result, the contents of the first registered term list 211 will be updated.

Returning to FIG. 4, the voice recognition server 200 updates the contents of the first registered term list 211 based on the update instruction received from the information processing device 100A. Although not shown, if the user of the information processing device 100A subsequently speaks to the user of the information processing device 100B, the data is converted into voice data by the function of the control unit 120 of the information processing device 100A. Then, the voice data is transmitted to the voice recognition server 200. Then, the term registration process is performed on the information processing device 100B side, and the content of the first registered term list 211 in the voice recognition server 200 is updated. Such processing will be repeatedly executed until the conversation such as the conference or lecture is completed. In this way, since the term registration process is performed for each conversation and the contents of the first registered term list 211 are updated, the dictionary for voice recognition is updated in real time, and the dictionary for voice recognition is preferably used. Can be generated. In this embodiment, a conversation between two parties is taken as an example, but the same applies to three or more parties. Further, the dictionary generated in this way can also be used as a dictionary in known Japanese input software.

(Modification example)
The present invention is not limited to the above embodiment, and various modifications and applications are possible. For example, the information processing apparatus 100 does not have to have all the technical features shown in the above-described embodiment, and has been described in the above-described embodiment so as to solve at least one problem in the prior art. It may have a structure of parts. In addition, at least a part of each of the following modifications may be combined.

In the above embodiment, an example is shown in which the process of step S107 in FIG. 5 is executed in the term registration process, but once at the timing when a series of conversations such as the end of a meeting or the end of a lecture are completed. It may be done. For example, the process of step S107 shown in FIG. 5 may be executed by the user performing an operation on the input / output unit 130 at the timing when the conversation ends. Further, for example, when a predetermined specific voice (a plurality of settings may be set) such as "end" is received, it is determined that the conversation is finished and the process of step S107 of FIG. 5 is executed. May be good. Further, unlike this, the process of step S107 of FIG. 5 may be executed every time a number of word information set by the user is registered in the registered term list 111. According to these, it is possible to reduce the load on the update process of the first registered term list 211.

Further, for example, the word "PoC" may be read differently for each user, such as a user who reads "POC" or a user who reads "Pock". With respect to such words, a plurality of voice data corresponding to one text data are registered in advance as the second registered term list 212, and in step S106 of FIG. 5, a plurality of voice data corresponding to one text data are registered. The voice data may be registered in the registered term list 111. Then, in the process of step S107, an instruction to update the first registered term list 211 may be given according to the contents. According to this, even when the reading of one word is different for each user, it is possible to preferably generate a dictionary for voice recognition.

Further, the information processing device 100 may include the configuration of the voice recognition server 200 according to the above embodiment. In this case, in step S107 of FIG. 5, the first registered term list 211 stored in the own storage unit 110 is updated to synchronize with the first registered term list 211 stored in the other information processing apparatus 100. It should be.

In addition, when the above-mentioned function is realized by sharing the OS (Operating System) and the application, or by cooperating with the OS and the application, only the part other than the OS may be stored in the medium.

It is also possible to superimpose a program on a carrier wave and distribute it via a communication network. For example, the program may be posted on a bulletin board system (BBS, Bulletin Board System) on a communication network, and the program may be distributed via the network. Then, by starting these programs and executing them in the same manner as other application programs under the control of the operating system, the above-mentioned processing may be executed.

1 Information processing system, 100, 100A, 100B Information processing device, 110, 210 Storage unit, 111 Registered term list, 112 Registration classification, 120, 220 Control unit, 121 Confidence comparison unit, 122 Morphological element extraction unit, 123 Part code estimation unit , 124 term classification unit, 125 term registration unit, 130, 230 input / output unit, 140, 240 communication unit, 200 voice recognition server, 211 first registered term list, 212 second registered term list, 221 voice recognition processing unit, 222 Confidence calculation unit, 510 network

Claims (6)

A voice recognition result receiving means for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence receiving means and
A word information registration means for registering word information included in the second voice recognition result when the first certainty degree and the second certainty degree are compared and a predetermined condition is satisfied is provided.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
An information processing device characterized by this. When the predetermined conditions are satisfied, an extraction means for extracting word information to be registered from the second voice recognition result according to a predetermined standard is further provided.
The word information registration means registers the word information extracted by the extraction means.
The information processing apparatus according to claim 1. Further provided with a classification means for classifying the word information extracted by the extraction means into one of a plurality of predetermined classifications for each occurrence frequency.
The word information registration means registers word information classified by the classification means for each classification.
The information processing apparatus according to claim 2. The word information includes voice information and character information.
A first dictionary update means for updating the first dictionary by adding the word information registered by the word information registration means to the first dictionary is further provided.
The second dictionary is newly stored by the operation of the user every time the first dictionary is updated.
The information processing apparatus according to any one of claims 1 to 3. A voice recognition result receiving step for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence reception step and
A word information registration step of comparing the first certainty degree and the second certainty degree and registering the word information included in the second voice recognition result when a predetermined condition is satisfied is provided.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
An information processing method characterized by this. Computer,
A voice recognition result receiving means for receiving a first voice recognition result based on the first dictionary and a second voice recognition result based on a second dictionary different from the first dictionary.
Receives the first certainty of the first voice recognition result calculated based on a predetermined calculation and the second certainty of the second voice recognition result calculated based on the calculation. Confidence receiving means,
When the first certainty degree and the second certainty degree are compared and a predetermined condition is satisfied, the word information included in the second voice recognition result is registered as a word information registration means.
The second dictionary includes word information specified by the user in addition to the word information registered in the first dictionary.
A program characterized by that.

Images