JP2001083982A - Speech recognition device, recording medium having data for speech recognition recorded therein and speech recognition navigation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a speech recognition device capable of recognizing even a long word easily and surely, a recording medium having data therefor recorded therein, and a speech recognition navigation device. SOLUTION: In this speech recognition navigation device for executing voice recognition of a facility name, by receiving designation of the facility name by a speech, a first recognition word of the whole reading of the facility name and a second recognition word of reading from the head of the facility name to the middle thereof are prepared in a recognition dictionary 210. Even if only voice data up to the middle can be acquired, because a user hems and haws the facility name in the middle when uttering the name, relation with the second recognition word is taken to thereby succeed speech recognition.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to voice recognition and a voice recognition navigation device.

[0002]

2. Description of the Related Art The present location of a car is displayed, and a wide area
2. Description of the Related Art In-vehicle navigation devices (hereinafter, referred to as navigation devices) that perform detailed display and guide a traveling direction and a remaining distance to a destination are known. Further, as one function of the navigation device, a so-called voice recognition navigation device for improving the safety of the driver by giving an operation instruction from the driver while driving is also known (for example, JP-A-09-292255).

[0003] Speech recognition software used in a speech recognition navigation device generally determines that speech has ended when speech has disappeared from the start of speech, and recognizes sound data and a recognition dictionary from the start of speech to the time when speech has disappeared. Calculate correlation values with all recognized words in. As a result, the recognition word having the maximum correlation value is determined as the recognition result. There are various types of words recognized by the voice recognition navigation device, such as a navigation command (3D display, enlargement, reduction, etc.) for instructing various navigation operations, a station name, a golf course name, a hospital name, a ski resort name, and the like.

[0004]

Among these words, long ones such as a golf course name, a hospital name, a ski resort name, etc.
There was a problem that it was very difficult to recognize compared to short words such as navigation commands and station names.

It is an object of the present invention to provide a speech recognition apparatus capable of easily and reliably recognizing long words, a recording medium for recording data for the speech recognition apparatus, and a speech recognition navigation apparatus.

[0006]

DETAILED DESCRIPTION OF THE INVENTION The present invention will be described below with reference to the embodiment shown in FIG. In order to achieve the above object, the invention according to claim 1 includes a voice input means (201), a storage means (210) for storing a recognition word corresponding to a word to be recognized and representing a reading of the word, A speech recognition device including speech recognition processing means for performing speech recognition processing by comparing the sound data obtained by the input means with speech recognition data generated based on the recognition word; (210) a first recognized word corresponding to the entire reading of the speech recognition target word, and a second recognized word corresponding to only a predetermined length reading from the beginning of the entire reading of the speech recognition target word. In both cases, the recognition word is stored as a recognition word of the word to be subjected to speech recognition. The invention of claim 2 is
2. A speech recognition apparatus according to claim 1, wherein said storage means comprises:
0) is changed to a second predetermined length reading from the beginning of the entire reading of the speech recognition target word when the entire reading of the speech recognition target word is longer than or equal to the first predetermined length. The second recognition word corresponding to only the speech recognition target word is stored as the recognition word of the speech recognition target word. According to a third aspect of the present invention, there is provided a voice recognition navigation apparatus according to the first or second aspect, (200), a map information storage means (108) for storing map information, and at least a voice recognition apparatus (200).
And control means (105) for performing control for the route guidance based on the recognition result and the map information. 5. A computer-readable recording medium according to claim 4, wherein a recognition word corresponding to a speech recognition target word for generating speech recognition data to be compared with sound data obtained by a speech input means in speech recognition processing. A first recognized word corresponding to the entire reading of the speech recognition target word and a second recognized word corresponding to only a predetermined length reading from the beginning of the entire reading of the speech recognition target word. Is recorded as data that is used as a recognition word for a word to be subjected to speech recognition.

In the section of the means for solving the above-mentioned problems, the description is made in correspondence with the drawings of the embodiments for easy understanding, but the present invention is not limited to the embodiments.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS First Embodiment FIG. 1 shows a first embodiment of a vehicle-mounted navigation system according to the present invention.
It is a figure showing composition of an embodiment. The in-vehicle navigation system includes a navigation device 100 and a voice unit 200. In the navigation system according to the first embodiment, voice recognition is surely successful even when the facility name is long.

A navigation device 100 includes a GPS receiver 101, a gyro sensor 102, and a vehicle speed sensor 10.
3, the driver 104, the CPU 105, and the RAM 10
6, ROM 107, and CD-ROM drive 108
, A display device 109, a bus line 110, and the like.

The audio unit 200 includes a microphone 201,
An A / D converter 202, a D / A converter 203, an amplifier 204, a speaker 205, a speech switch 206,
A driver 207, a CPU 208, a RAM 209,
It comprises a ROM 210, a bus line 212 and the like.
The navigation device 100 and the audio unit 200 are connected via a communication line 211.

The GPS receiver 101 has a GPS (Global P
ositioning System) Receives signals from satellites and detects the absolute position and azimuth of the vehicle. Gyro sensor 102
Is constituted by, for example, a vibrating gyroscope, and detects the yaw angular velocity of the vehicle. The vehicle speed sensor 103 detects the moving distance of the vehicle based on the number of pulses output every time the vehicle travels a predetermined distance. The two-dimensional movement of the vehicle can be detected by the gyro sensor 102 and the vehicle speed sensor 103. The driver 104 includes a GPS receiver 101, a gyro sensor 102, a vehicle speed sensor 103
Is a driver for connecting the signal from the bus line 110 to the bus line 110. That is, each sensor output is output to the CPU 1
05 is converted to readable data.

The CPU 105 controls the entire navigation device 100 by executing a program stored in the ROM 107. The RAM 106 is a volatile memory and secures a work data area. ROM 107
The nonvolatile memory stores the above-described control program and the like. The CD-ROM drive 108 uses a CD-ROM as a recording medium and stores road map information such as vector road data. The CD-ROM drive may be a DVD drive using a DVD as a recording medium or another recording device. The display device 109 displays a road map of the current location and the surrounding area of the car, route information to the destination, information of the next guidance intersection, and the like. For example, it is composed of a liquid crystal display device or a CRT. The bus line 110 is connected to the navigation device 10.
0 is a line for connecting components such as the CPU 105 via a bus.

The voice unit 200 performs voice-related processing such as voice recognition and voice synthesis. Speech switch 206
Is a switch for instructing the start of voice recognition when pressed by the user. Input of sound data is performed via the microphone 201 for a predetermined time after the utterance switch 206 is pressed. The input sound is converted into digital audio data by the A / D converter 202 and the driver 207.

In the ROM 210 of the audio unit 200,
A speech recognition software (program), a speech synthesis software (program), a speech recognition dictionary (hereinafter simply referred to as a recognition dictionary), a speech synthesis dictionary (hereinafter simply referred to as a synthesis dictionary), and the like are stored. The voice recognition software calculates a correlation value between the digital voice data and all the recognized words in the recognition dictionary, and obtains a recognized word having the highest correlation value as a recognition result. The speech synthesis software calculates data for causing a specified sentence to be uttered from a speaker. Since the contents of both softwares are publicly known, detailed description will be omitted.

[0015] The recognition dictionary is a set of data obtained by collecting a plurality of words (words) to be subjected to speech recognition. Specifically, reading data of each word specified by Hiragana, Katakana, or Romaji (actually, its character code) is stored. The words stored in the recognition dictionary are called recognized words. Each recognition word is accompanied by information such as character data of the word as well as reading data and coordinate information in the case of a facility name. Details of the recognition dictionary will be described later. The synthesis dictionary stores sound source data and the like necessary for speech synthesis.

At the end of the utterance, the CPU 208
9. Execute voice recognition software using the ROM 210 or the like to perform voice recognition of digital voice data. Speech recognition software generates speech recognition data for recognition words while referring to the recognition data of the recognition words in the recognition dictionary (data specified in Hiragana, Katakana, or Romaji), and calculates the correlation value with the digital speech data I do. The correlation values with the digital voice data are calculated for all the recognized words, and the recognized words having the highest correlation value and the predetermined value or more are determined, and the speech recognition is completed. The echo-back word linked to the recognition word is converted into utterance data using speech synthesis software. Then D
Using the / A conversion unit 203, the amplifier 204, and the speaker 205, the recognition result is output as an echo back.

If any of the calculated correlation values is equal to or less than a predetermined value, it is determined that voice recognition has not been performed, and no navigation operation is performed. More specifically, a beep sound indicating recognition failure such as “puppy” is sounded, and a response (echo back) indicating “unrecognizable” is made. The bus line 212 is a bus line of the audio unit 200.

Next, the recognition dictionary will be described in detail.
FIG. 2 is a diagram showing a golf course recognition dictionary in which recognition words relating to ten golf course names are stored. The recognition word is read data relating to the name of the facility (in FIG. 2, the name of the golf course). In FIG. 2, characters including kanji are described for easy understanding. However, corresponding character codes are designated by hiragana, katakana, or romaji and stored. Each recognition word has accompanying information. The supplementary information stores various information such as coordinate information on the map of the facility, the number of the recognition dictionary to be read next, attribute information of the facility, and character data for displaying the facility name. In FIG. 2, only coordinate information is shown as a representative.

In the example of the golf course recognition dictionary shown in FIG. 2, analysis is made on the fact that the probability of recognition failure being high in the case of a long golf course name (word) is high. For example, if the user
Suppose that the second golf course name "Mitahara Golf Club Matsuda Course" is uttered and it is recognized by voice. Not all users utter this long word at once. Some users take a break on the way and then talk. For example, it is assumed that the user once stops at “Mitahara Golf Club” and then speaks “Matsuda Course”. If the pause time is short, the voice recognition software treats the sound data "Mitawara Golf Club Matsuda Course" as one input. Therefore, it can be correctly recognized and there is no problem.

However, the speech recognition software generally determines that the utterance has ended when the utterance disappears from the start of the utterance.
If the utterance time is long, it is determined that the utterance has ended when the utterance is stopped, and the utterance data resumed after the utterance is discarded. That is, only the sound data “Mitawara Golf Club” is used as input. As a result, especially when many similar words exist, the probability of erroneous recognition becomes extremely high.

As a result of the above analysis, in the first embodiment, the golf course recognition dictionary of FIG. 2 will be described below. In the above-mentioned "Mitawara Golf Club Matsuda Course", in most cases, it is expected that a short break will occur between "Mitahara Golf Club" and "Matsuda Course". Therefore, "Mitawara Golf Club" for "Mitahara Golf Club Matsuda Course"
Is added. The supplementary information is the same coordinate information 3 as “Mitahara Golf Club Matsuda Course”. In this way, another word recognition word prepared for a normal recognition word is called a “paraphrase word”.

FIG. 3 is a diagram showing an example in which paraphrases are added to the golf course recognition dictionary of FIG. For "Atsumoto Kokusai Country Club", the paraphrase of "Atsumoto Kokusai", for "Mitakyu Fujisawa Golf Club", the paraphrase of "Mitakyu Fujisawa", and for "Mitahara Yumoto Country Club", "Mitahara A paraphrase such as "Yumoto" and a paraphrase such as "Daiatsuhon Country Club" for "Daitsuhon Country Club Book Course" are added and stored in the same recognition dictionary.

For example, when uttering "Daiatsuhon Country Club Hon Course", even if a sound can be input only as "Daiatsuhon Country Club" as a result of worrisomeness,
Since a short recognition word "Daikouhon Country Club" is prepared, recognition can be successful. In this way, for a long word, if a paraphrase from a regular recognition word to a place where a delimiter is good is prepared and added to the recognition dictionary, the recognition can be surely succeeded even when the user stops speaking in the middle. be able to. This has the disadvantage that the capacity of the recognition dictionary increases and the recognition execution time increases, but there is a great advantage that erroneous recognition due to stagnation can be reliably reduced even with a long facility name.

As the paraphrase, only long words having a predetermined length or more may be selected and prepared. Also,
Regardless of the length of words, only words that are likely to cause stagnation may be selected and prepared empirically. Further, a plurality of paraphrases having different lengths may be prepared for the regular recognition word.

The way to determine the delimiter when creating a short paraphrase may be determined in advance by considering the most likely occurrence of stagnation based on experiments and experiences. In addition, since a long word is generally a group of a plurality of short words, for example, a position of a short word break closest to a position of exactly half of the entire reading may be used as the break. Alternatively, it is also conceivable to determine unconditionally by the break of a few short words from the beginning. Further, it may be unconditionally divided at a few syllables from the beginning.

FIG. 4 is a diagram showing a flowchart of control for performing voice recognition in the voice unit 200. The control program is stored in the ROM 210 and the CPU 208
Executes the control program. This routine starts when the navigation device 100 and the audio unit 200 are turned on.

In step S1, it is determined whether or not the utterance switch 206 has been pressed. If the utterance switch 206 has been pressed, the process proceeds to step S2. If the button has not been pressed, this routine ends. After pressing the utterance switch 206, the user utters, for example, the golf course name shown in FIG.
In step S2, the audio signal from the microphone 201 is converted into digital audio data. In step S3, it is determined whether or not the utterance has ended. The end of the utterance is determined to be the end of the utterance when the audio signal is interrupted for a predetermined time. If it is determined that the utterance has ended, the process proceeds to step S4, and if it is determined that the utterance has not ended, the process returns to step S2.

In step S4, correlation values are calculated for the digital speech data obtained in step S2 and all the recognized words in the recognition dictionary shown in FIG. 3, and the process proceeds to step S5. As the recognition dictionary, the recognition dictionary of FIG. 3 in which paraphrases are added to the recognition dictionary of FIG. 2 is used. In step S5, it is determined whether the highest correlation value among the calculated correlation values is equal to or greater than a predetermined value. If the value is equal to or more than the predetermined value, it is determined that the word has been recognized and the process proceeds to step S6. In step S6, the recognized word having the highest correlation value is echoed back by voice.

Further, in step S6, the navigation device 1 recognizes that the corresponding golf course name (facility name) has been recognized.
After notifying 00, the process ends. When notifying the navigation device 100, the character information of the accompanying information and the coordinates on the map are notified. Navigation device 100
Displays a road map near the relevant facility on the display device 109 based on the coordinate data on the map of the relevant golf course (facility) transmitted via the communication line 211 and the map information of the CD-ROM drive 108. .

On the other hand, if the highest correlation value is less than the predetermined value in step S5, it is determined that the uttered word cannot be recognized, and the process proceeds to step S7. In step S7, the voice is echoed back saying "unrecognizable"
The process ends. The navigation device 100 does not perform any processing.

As described above, when performing voice recognition, a recognition dictionary to which paraphrases are added is used. Thereby, when speaking a long facility name or the like, speech recognition of the long facility name can be surely succeeded, even if it says halfway.

-Second Embodiment-An in-vehicle navigation system according to a second embodiment comprises:
Even if the utterance is made immediately after pressing the utterance switch, the voice recognition is surely succeeded. The configuration of the vehicle-mounted navigation system according to the second embodiment is the same as that of the vehicle-mounted navigation system according to the first embodiment shown in FIG.

Since the recognition dictionary is different from that of the first embodiment, the recognition dictionary will be described below. FIG.
FIG. 4 is a diagram showing a station name recognition dictionary storing recognition words relating to five station names. Each recognition word has accompanying information.
The recognition word is read data on the facility name (station name). The recognition word is designated by Hiragana, Katakana, or Roman alphabet, and its character code is stored. In FIG.
The case of Hiragana is shown. The sound indicated by one kana character is called one syllable. The incidental information includes information on display data to be displayed on the navigation device (character data for display of a station name in FIG. 5), information on coordinates of facilities on a map,
Information on navigation operation commands, information on echo back data, and the like. FIG. 5 representatively shows display character data and coordinate information.

In the example of the station name recognition dictionary shown in FIG. 5, an analysis will be made on the fact that recognition is highly likely to fail when uttering immediately after pressing the utterance switch 206.

The speech recognition software generally presses the utterance switch 206, and thereafter calculates a correlation value between the sound data uttered by the user and all the recognized words in the recognition dictionary. As a result, the recognition word having the maximum correlation value is determined as the recognition result. The voice recognition software requires some preparation time until the voice via the microphone 201 is accepted after the speech switch 206 is pressed. Therefore, when the user speaks immediately after pressing the speech switch 206, at the worst, the head of the spoken word may be slightly omitted. For example, if the station name "Sobudai-mae" is uttered immediately after pressing the utterance switch 206, the consonant of the first word "So" may be omitted so that "Obudai-mae" is heard. As a result, especially when there are many similar words, the probability of erroneous recognition becomes extremely high.

As a result of the above analysis, in the second embodiment, the station name recognition dictionary shown in FIG. 5 will be described below. For example, suppose that when considering a recognition word for a station name of “Sobudai Mae”, the leading “So” is omitted. In this case, as described above, there may be a case where it is heard that "there is nothing". Therefore, in place of the head "so", a recognition word "Obudaimae" paraphrased with the vowel "O" is added to the recognition dictionary. The supplementary information is attached to the same supplementary information as the regular "Sobudaime". As a result, immediately after pressing the utterance switch 206, "Sobudaime" is uttered, and even if the worst leading consonant is missed, the speech recognition can be surely succeeded. In addition, another word recognition word prepared for a normal recognition word is referred to as a “paraphrase word”.

Considering the recognition word of the station name "Odaki Sagamihara", it is assumed that the leading "O" is omitted. In this case, it may be heard as "Dakyusagamihara". Therefore, a paraphrase of the recognition word "Dakyusugamihara" from which the leading "O" is deleted is added to the recognition dictionary. The supplementary information is the same as the regular supplementary information "Odakyu Sagamihara". As a result, immediately after pressing the utterance switch 206, "Odakyu Sagamihara" is uttered, and even if the leading "O" is missed, the speech recognition is surely succeeded.

FIG. 6 is a diagram showing an example of a case where a paraphrase is added to the station name dictionary of FIG. Rules for creating paraphrases include, for example, paraphrasing the first word with its vowel, especially if it is a consonant, and paraphrasing it with words with a certain number of words removed from the beginning. It is conceivable to paraphrase with a word in which only the first word is deleted, or paraphrase with a word in which the vowel is deleted only when the first word is a vowel. Further, when the utterance is made immediately after pressing the utterance switch 206, a paraphrase that can be heard experimentally or empirically may be added. A plurality of paraphrases may be prepared for a regular recognition word. Here, the "word" in the case of "the first word" means one word (one syllable) of the Japanese syllabary.

The flowchart of the control for performing the speech recognition according to the second embodiment is the same as that of FIG. 4 of the first embodiment except for the recognition dictionary used, and therefore the description thereof is omitted.
The recognition dictionary uses the recognition dictionary of FIG. 6 to which the paraphrase is added.

As described above, the head word of the regular recognition word or a paraphrase in which some words are deleted from the head or paraphrased into vowels are added to the recognition dictionary. Thus, even if the user speaks immediately after turning on the speech switch 206, it is possible to surely succeed in the speech recognition of the word.

-Third Embodiment- A vehicle-mounted navigation system according to a third embodiment comprises:
For example, regardless of whether "street" is uttered as "tori", "street", or "tori", voice recognition is surely succeeded. The configuration of the vehicle-mounted navigation system according to the third embodiment is the same as that of the vehicle-mounted navigation system according to the first embodiment shown in FIG.

Since the recognition dictionary is different from that of the first embodiment, the recognition dictionary will be described below. FIG.
FIG. 4 is a diagram showing a station name recognition dictionary storing recognition words relating to four station names. Each recognition word has accompanying information.
The recognition word is read data on the facility name (station name). The recognition word is designated by Hiragana, Katakana, or Roman alphabet, and its character code is stored. In FIG.
The case of katakana is shown. The sound indicated by one kana character is called one syllable. The supplementary information includes information on display data to be displayed on the navigation device (character data for displaying station names in FIG. 7), information on coordinates of facilities on a map,
Information on navigation operation commands, information on echo back data, and the like. FIG. 7 shows display character data and information numbers as representatives.

In the example of the station name recognition dictionary shown in FIG. 7, analysis will be made on the fact that the probability of recognition failure being high when, for example, speaking "Meidaimae" is high. Since the kanji reading of "Meidaimae" is "Meidaimae", recognition words for "Meidaimae" are prepared. However, "Meidaimae" is replaced by "Meidaimee"
Or many people say "Maedai Mae". In such a case, the correlation value with the recognition word of “Maydai Mae” decreases, and particularly when many similar words exist, the probability of erroneous recognition increases.

As a result of the above analysis, in the third embodiment, the station name recognition dictionary shown in FIG. 7 will be described below. For example, when considering the above recognition words for the station name “Meidaimae”, “Meidaimae” and “Meidaimae”
Prepare two recognition words. For the recognition word of the station name “Chofu”, two recognition words “Choufu” and “Chooff” are prepared. In addition, the recognition word of another wording prepared about the recognition word of a regular reading is called a "paraphrase word." As the supplementary information of the paraphrase, the same information as the regular recognition word is specified.

From the above, the following rule is found. In the case of a reading word in which "I" follows the Japanese syllabary word (syllable) such as "e", "ke", "se", "te", and "ne", the "i" is changed to "e" Many people speak as if they were replaced. In addition, in the case of reading words in which "U" follows the word (syllable) such as "o", "ko", "so", "to", "no", "u" is replaced with "o" Many people speak like this.

Therefore, a recognition word according to this rule is added. The station name dictionary of FIG. 8 is obtained by adding recognition words to the station name dictionary of FIG. 7 according to the above rule. As a result, the station name of “Meidaimae” can be reliably recognized even if “Meidaimae” is spoken as “Meidaimae”, which is generally spoken in conversation, unlike the literal reading “Meidaime”.

It should be noted that instead of replacing "e" or "o", it may be replaced with a long code "-". Alternatively, both the recognition word replaced with “e” or “o” and the recognition word replaced with the long code “-” may be added.

The above is the case of the speech recognition system in which the reading is specified in hiragana or katakana. However, the same applies to the case of specifying in Roman characters. For example,
"Meidaimae" is a regular recognition word in Roman characters
aimae ". Replace “i” following “e” with “e” and add a recognition word “meedaimae”. "Chofu"
, "Chouhu" is specified as a regular recognition word. Replace "u" following "o" with "o" and "choohu"
And

Next, consider the word "Tomei Expressway". Since this reading is “Popularity”, if the above rule is applied, there are four parts to be replaced. Considering these four combinations, it is necessary to add 15 new recognition words. For this reason, the size of the recognition dictionary becomes enormous, and an enormous amount of R
OM210 is required. As a countermeasure, one is to store the recognition dictionary in the ROM 210 instead of storing it in the CD-RO.
A large-capacity recording medium such as M or DVD-ROM may be used.

As another countermeasure, the following contents can be considered. The ROM 210 prepares a recognition dictionary storing only recognition words of regular reading. When the speech recognition software uses the recognition dictionary for the speech recognition processing, a predetermined program is executed, so that the paraphrase based on the above rule based on the recognized word of the regular reading is stored in the RAM 20.
9 may be generated. Since this RAM 209 is a work memory area, when another recognition dictionary is used, the previously created paraphrase is cleared and a paraphrase based on another recognition dictionary is newly generated on the RAM 209. This eliminates the need for a huge amount of ROM. In addition, since it is sufficient to create only data in which the kanji is read as it is in the ROM 210, it is easy to create a recognized word. If a program that converts kanji to kana is used, a recognition dictionary with only regular readings can be easily created by automation or semi-automation.

The flowchart of the control for performing the voice recognition according to the third embodiment is the same as that of FIG. 4 of the first embodiment except for the recognition dictionary used, and therefore the description thereof is omitted.
As the recognition dictionary, the recognition dictionary of FIG. 8 to which the paraphrase is added is used.

As described above, if the vowel is followed by “A” in the recognized word of the normal reading, it is replaced with “E” or “A”, and if the vowel continues with “O”, it is replaced by “O” or “O”. Is newly added. As a result, a recognition word close to the actual utterance is prepared, and the probability of successful speech recognition increases.

In the third embodiment, when there are many combinations of replacement words and a large number of replacement words are required, a predetermined program is executed when speech recognition processing is performed, so that the recognition words of normal reading can be obtained. An example in which a recognized word of a paraphrase is generated based on the case ("Tomei Expressway") is shown.
This content can be applied even when there are not many paraphrased words (for example, in the case of “Meidaimae” described above). Further, a case where a paraphrase is generated in the first embodiment (for example, in the case of the above-mentioned "Mitahara Golf Club Matsuda Course") and in the second embodiment (for example, in the case of the above-mentioned "Soubu-Daimee") Also applicable to

In the first to third embodiments, the in-vehicle navigation system has been described. However, the present invention is not limited to this. The present invention can be applied not only to a vehicle-mounted device but also to a portable navigation device. Furthermore, the present invention is applicable not only to navigation devices but also to all devices that perform voice recognition.

In the first to third embodiments, the navigation device 100 and the audio unit 200 have been described as being separated from each other. However, the present invention is not limited to this. It may be configured as one navigation device including a sound unit inside. Further, the control program, the recognition dictionary, and the like can be provided on a recording medium such as a CD-ROM. Furthermore, it is also possible to provide a control program, a recognition dictionary, and the like on a recording medium such as a CD-ROM, and realize the system on a computer such as a personal computer or a workstation.

In the first to third embodiments, when the search of the facility name is successfully performed by the voice unit 200, the content is notified to the navigation device 100, and the navigation device 100 performs one of the navigation processes such as road guidance. Although an example of displaying a map near the facility has been described, the present invention is not limited to this example. Navigation device 10
In the case of 0, a route search, a route guidance and other various navigation processes can be considered based on the result of a successful search by the voice unit 200.

[0057]

Since the present invention is configured as described above, it has the following effects. Claims 1 and 5
Since the invention of the present invention also includes a shortened recognition word corresponding to only a predetermined length of reading from the beginning of the entire reading of the speech recognition target word, for example, when uttering a long facility name, In other words, it is possible to surely succeed in the speech recognition of the long facility name. According to the second aspect of the present invention, the shortened recognition word is provided only when the entire reading of the speech recognition target word is longer than a predetermined length, so that the memory capacity of the recognition dictionary can be increased to a minimum. Claim 3
According to the invention, the above-mentioned effect can be effectively exhibited particularly when performing navigation such as road guidance in a voice recognition navigation device.

[Brief description of the drawings]

FIG. 1 is a diagram showing a configuration of an on-vehicle navigation system of the present invention.

FIG. 2 is a diagram illustrating a recognition dictionary before improvement according to the first embodiment.

FIG. 3 is a diagram illustrating an improved recognition dictionary according to the first embodiment.

FIG. 4 is a diagram showing a flowchart of control for performing voice recognition in the first embodiment.

FIG. 5 is a diagram showing a recognition dictionary before improvement in a second embodiment.

FIG. 6 is a diagram illustrating an improved recognition dictionary according to the second embodiment.

FIG. 7 is a diagram illustrating a recognition dictionary before improvement in a third embodiment.

FIG. 8 is a diagram illustrating an improved recognition dictionary according to the third embodiment.

[Explanation of symbols]

 REFERENCE SIGNS LIST 100 Navigation device 101 GPS receiver 102 Gyro sensor 103 Vehicle speed sensor 104 Driver 105 CPU 106 RAM 107 ROM 108 CD-ROM drive 109 Display device 110 Bus line 200 Audio unit 201 Microphone 202 A / D conversion unit 203 D / A conversion unit 204 Amplifier 205 speaker 206 utterance switch 207 driver 208 CPU 209 RAM 210 ROM 211 communication line 212 bus line

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 2F029 AA02 AB01 AB07 AB09 AC01 AC02 AC04 AC18 5D015 GG03 KK02 5H180 AA01 BB13 FF04 FF05 FF22 FF25 FF27 FF33

Claims (4)

[Claims] 1. A voice input means, a storage means for storing a recognition word corresponding to a word to be recognized and representing a reading of the word, a generation based on the sound data obtained by the voice input means and the recognition word And a voice recognition processing unit that performs a voice recognition process by comparing the obtained voice recognition data with the obtained voice recognition data, wherein the storage unit stores a first voice corresponding to the entire reading of the voice recognition target word. A recognition word and a second recognition word corresponding to only a reading of a predetermined length from the beginning of the entire reading of the speech recognition target word are both stored as recognition words of the speech recognition target word. A speech recognition device characterized by the above-mentioned. 2. The speech recognition apparatus according to claim 1, wherein said storage means stores the speech recognition target word when the entire reading of the speech recognition target word is longer than a first predetermined length. A second recognition word corresponding to only a reading of a second predetermined length from the beginning of the entire reading of the speech as a recognition word of the speech recognition target word. 3. A voice recognition device according to claim 1 or 2, a map information storage means for storing map information, and control for route guidance based on at least a recognition result of said voice recognition device and said map information. And a control means for performing the following. 4. In the speech recognition processing, data relating to a recognition word corresponding to a speech recognition target word for generating speech recognition data to be compared with sound data obtained by the speech input means, A first recognition word corresponding to the entire reading of the word of the word and a second recognition word corresponding only to a reading of a predetermined length from the beginning of the entire reading of the word to be speech-recognized. A computer-readable recording medium on which data used as a recognition word of the speech recognition target word is recorded.