JP4654889B2 - Playback device - Google Patents

Description

  The present invention relates to a technique for showing a learner the difference between a sound as a model and a sound emitted by a learner.

In language learning, when practicing pronunciation, a learning method is widely used in which a model voice recorded on a recording medium such as a CD (Compact Disk) is reproduced and pronounced by imitating the model voice. . The purpose of this is to acquire correct pronunciation by imitating model voices. When performing such learning, the learner objectively grasps his / her pronunciation, recognizes the difference from the model voice, and improves the pronunciation. Is the same pronunciation as the model voice? It is difficult for the learner to grasp the objection objectively by listening to his / her pronunciation. Thus, for example, as disclosed in Patent Document 1, a technique has been devised that enables a learner to objectively grasp his / her voice. The language learning device disclosed in Patent Literature 1 extracts vowels from the learner's voice and graphs the extracted vowel pitches and utterance times.
JP-A-5-232856

  Now, it is said that in order to perform correct pronunciation, it is important to match dynamic changes such as the pitch and rhythm of pronunciation with the model voice. According to the technique disclosed in Patent Document 1, since static data such as vowel pitch, speech time, and pronunciation timing is graphed, the learner can objectively grasp his / her voice. However, only static data is displayed, and for example, it is difficult to grasp dynamic changes in pronunciation such as pronunciation rhythm. There is a problem that it is difficult to grasp the dynamic difference in pronunciation rhythm and to find out which point should be improved.

  The present invention has been made under the above-described background, and an object thereof is to enable a learner to understand the difference between a learner's voice rhythm and a model voice rhythm.

  In order to solve the above-described problems, the present invention is configured to store sound data corresponding to a sound to be sounded by dividing the sound data into predetermined sections, and to read the sound data from the storage means and perform reproduction processing. Reproducing means, sound collection data generating means for generating data corresponding to the collected sound as sound collection data, recognizing a portion corresponding to the sound data delimiter for the sound collection data, and corresponding delimiter Synchronizing with the reproduction processing by the reproducing means, the position adding means for adding, the display means for displaying the scale formed by connecting the display sections having the display width corresponding to the time length of each section, the sound data First display control means for displaying the reproduction position in each section of the scale for each display section of the scale, sound collection data reproduction processing means for reproducing the sound collection data, and the sound collection data And second display control means for displaying the reproduction position in each section of the collected sound data divided by the position adding means for each display section of the scale in synchronization with the reproduction processing means. Is provided.

  In this aspect, the storage means stores a plurality of different sound data, and has a selection means for selecting one of the plurality of sound data stored in the storage means, and the reproduction means is selected by the selection means. The reproduced sound data may be read from the storage means and reproduced.

  According to the present invention, the learner can grasp the difference between the rhythm of the learner's voice and the rhythm of the model voice.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[Configuration of the embodiment]
FIG. 1 is a block diagram illustrating a hardware configuration of a language learning device 1 according to an embodiment of the invention. As shown in FIG. 1, each unit of the language learning device 1 is connected to a bus 101, and signals and data are exchanged between the units via the bus 101.

  The microphone 109 is connected to the sound processing unit 108, converts input sound into an electrical signal (hereinafter referred to as a sound signal), and outputs the electric signal to the sound processing unit 108. The speaker 110 is connected to the sound processing unit 108 and outputs a sound corresponding to the signal output from the sound processing unit 108. The audio processing unit 108 has a function of converting an audio signal input from the microphone 109 into digital data and outputting it, and a function of converting digital data representing audio into an analog audio signal and outputting the analog audio signal to the speaker 110. . Here, since the voice of the learner who uses the language learning device 1 is input to the microphone 109, the digital data of the voice signal converted by the voice processing unit 108 is referred to as learner data and is input to the microphone 109. The voice (the voice indicated by the learner data) is referred to as a learner voice.

  The display unit 106 includes, for example, a display device such as a liquid crystal display, and displays a character string, various messages, a menu screen for operating the language learning device 1, and the like under the control of the CPU 102. The input unit 107 includes an input device such as a keyboard and a mouse (both not shown), and outputs a signal corresponding to the operation content to the CPU 102 in response to a key press or a mouse operation.

  The storage unit 105 includes an HDD (Hard Disk Drive) device and stores various data. Specifically, the storage unit 105 stores learner data output from the voice processing unit 108. In addition, the storage unit 105 includes example sentence text data representing example sentences used for language learning, and digital data (hereinafter referred to as model voice data) representing voices (hereinafter referred to as model voices) when the native speaker reads the example sentences. ) Is remembered. The storage unit 105 stores the example sentence table TB1 in the format illustrated in FIG. 2, and the table corresponds to the example sentence text data, the file name of the model voice data, and the identifier for uniquely identifying each example sentence text data. It is attached and stored.

In addition, the storage unit 105 stores a pitch table TB2 having the format illustrated in FIG. 3 in correspondence with the stored example sentences. In the pitch table TB2, the identifier field stores an identifier for uniquely identifying example sentence text data. This identifier is the same as the identifier stored in the example sentence table TB1.
The frame number field stores a number indicating each frame when the exemplary voice of the example sentence specified by the identifier in the identifier field is divided in a predetermined time frame (frame) on the time axis. For example, when 1 frame = 100 msec, if the example voice “One centimeter is ten millimeters” is read out in 2.6 seconds, the voice is divided into 26 frames as shown in FIG. Is done. In the pitch table TB2, numbers 1 to 26 indicating the 26 frames are stored.

The pitch field stores pitch data indicating the pitch of the voice at each frame time of the model voice. For example, as shown in FIG. 4, when the pitch of the voice at the third frame on the time axis of the model voice is X, the frame number “3” is stored as shown in FIG. “X” is stored in the existing row.
The word field stores data indicating which frame corresponds to which word in the example sentence. For example, in “One centimeter is ten millimeters.”, The case where the first frame sound and the second frame sound on the time axis of the model sound correspond to the example sentence “One” is shown in FIG. In this way, the character string “One” is stored in the row where the frame numbers “1” and “2” are stored.

  In addition, the storage unit 105 stores a word table TB3 in the format illustrated in FIG. 5. In this table, an identifier indicating an example sentence, text data of each word included in the example sentence, and an utterance of each word The start time is stored in association with each other.

  A CPU (Central Processing Unit) 102 executes a program stored in a ROM (Read Only Memory) 103 using a RAM (Random Access Memory) 104 as a work area.

[Operation of the embodiment]
Next, the operation of this embodiment will be described.
First, when the learner performs an operation to instruct display of a list of example sentences, the CPU 102 reads out example sentence text data stored in the example sentence table TB1 (FIG. 6: step SA1), and displays a list of example sentences represented by the read data. The information is displayed on the display unit 106 (step SA2). Thereafter, when the learner operates the input unit 107 and performs an operation of selecting one of the displayed example sentences (step SA3; YES), the CPU 102 displays the screen displayed on the display unit 106, the input unit, and the like. Based on the signal sent from 107, the selected example sentence is specified (step SA4). When CPU 102 identifies the selected example sentence, CPU 102 reads out the file name of the model voice data stored in association with the selected example sentence in example sentence table TB1 (step SA5). For example, in the table shown in FIG. 2, when an example sentence with the identifier “001” is selected, the file name “a001” is read.

Next, the CPU 102 reads the model voice data specified by the read file name from the storage unit 105, and outputs the read model voice data to the voice processing unit 108 (step SA6). Further, the CPU 102 controls the display unit 106 to display the selected example sentence and the pitch of the example voice of the example sentence (step SA7). Here, since the example sentence with the identifier “001” is selected, the example sentence text data stored in the example sentence table TB1 in association with the identifier “001” is read, and the identifier “001” is stored. Pitch data is read from the pitch table TB2. Then, as shown in FIG. 7, the selected example sentence is displayed according to the read example sentence text data, and the pitch of the example voice of the example sentence is displayed according to the read pitch data.
In FIG. 7, the length of the displayed example sentence and the length of the pitch correspond to the entire playback time length of the model voice data, and the left end of the example sentence and the left end of the pitch display start playback of the model voice. The right end of the example sentence and the right end of the pitch display indicate the end point of reproduction of the model voice. The displayed pitch is displayed as a waveform connecting the pitches of the frames.

  When the model voice data is input to the voice processing unit 108, the model voice data which is digital data is converted into an analog signal and output to the speaker 110, and the model voice is reproduced from the speaker 110. When the reproduction of the model voice is started, the CPU 102 controls the display unit 106 to display the bar 10 indicating the portion of the displayed example sentence that is being reproduced (step SA8). For example, at the timing when the sound of the frame “3” portion (between 200 msec and 300 msec from the start of sound generation) is being reproduced, the CPU 102 changes the frame “3” as shown in FIG. The portion where the pitch is displayed is displayed so that the bar 10 moves over a time of 100 msec, and the sound of the portion of the frame “4” (between 300 msec and 400 msec when viewed from the start of sound generation) is reproduced. At the timing, as shown in FIG. 7B, the portion where the pitch of the frame “4” is displayed is displayed so that the bar 10 moves over the time of 100 msec. Thus, the horizontal display position of the bar 10 is controlled in synchronization with the frame number to be reproduced.

  When the reproduction of the model voice is finished, the CPU 102 controls the display unit 106 to display, for example, a message for prompting pronunciation of the example sentence such as “Press the key to pronounce and then press the key again when the pronunciation is finished” ( Step SA9). The learner listens to the model voice output from the speaker 110, and then operates the input unit 107 according to the message to read the example sentence by imitating the model voice. The learner's voice is converted into a voice signal by the microphone 109, and the converted signal is output to the voice processing unit 108. When the audio signal output from the microphone 109 is input, the audio processing unit 108 converts the audio signal into learner data that is digital data. This learner data is output from the voice processing unit 108 and stored in the storage unit 105.

  When the learner finishes pronunciation and operates the input unit 107 (step SA10; YES), the CPU 102 adjusts the length of the voice indicated by the learner data, the length of the model voice indicated by the model voice data, and the learner. The learner data is processed so that the length of the learner's voice indicated by the data is the same (step SA11). FIG. 8 is a diagram illustrating the waveform of the model voice and the waveform of the learner voice input to the microphone 109. In FIG. 8, the waveform of the model voice and the waveform of the learner voice are shown when the same example sentence is uttered, but the length of the voice waveform is different because the utterance speed is different. The CPU 102 analyzes the model voice data and the learner data, and obtains the length of the model voice and the length of the learner voice (Δt in FIG. 8). As shown in FIG. 8, when the length of the learner's voice is longer by Δt than the length of the model voice, a process of reducing the length of the learner's voice by Δt is performed.

  Next, the CPU 102 divides the waveform of the model voice and the waveform of the learner voice into a plurality of frames by dividing the waveform at a predetermined time interval (100 msec) as shown in FIG. Then, the speech waveform of each frame of the model speech and the speech waveform of each frame of the learner speech are associated using a DP (Dynamic Programming) matching method (step SA12). For example, in the waveform illustrated in FIG. 9, the model voice frame A1 is associated with the learner voice frame B1, and the model voice frame A3 is associated with the learner voice frame B4.

  When the association between the model voice and the learner voice ends, the CPU 102 divides each voice waveform for each word pronunciation (step SA13). Specifically, first, for the model voice, the utterance start time is read from the word table TB3. Here, since the example sentence selected by the learner is “One centimeter is ten centimeter.”, First, the utterance start time “0.0 sec” of “One” is read from the word table TB3. As shown in FIG. 9, the CPU 102 adds information indicating the word break (hereinafter referred to as word break information C) to the frame at the position of “0.0 sec” in the speech waveform (frame A1). Next, the CPU 102 reads the utterance start time “0.2 sec” of “centimeter” from the word table TB3, and adds the word break information C to the frame (frame A3) corresponding to the position 0.2 sec after the start of pronunciation.

  After adding the word break information C to the last word “millimeters” for the model voice, the CPU 102 then adds the word break information for the learner voice. First, the CPU 102 extracts a frame to which word break information is added in the model voice. Then, a frame corresponding to the extracted frame is specified in the learner's voice, and word break information C is added to the specified frame. For example, when the frame A1 to which the word break information C is added is extracted, the frame A1 is associated with the frame B1 by the process of step SA12 described above, so the CPU 102 determines that the frame B1 corresponds to the frame A1. And the word break information is added to the frame B1. Further, when the frame A3 to which the word break information is added is extracted, the frame A3 is associated with the frame B4 by the process of step SA12 described above, so the CPU 102 determines the frame B4 associated with the frame A3. Identify and add word break information C to this frame B4.

  When CPU 102 adds the word break information to the frame and divides the speech waveform for each pronunciation of the word, CPU 102 calculates the speech pitch and utterance time of each word for the learner speech (step SA14). For example, in the case of “One” of the learner's voice, voice waveforms from frame B1 to frame B3 are extracted as a voice waveform representing the pronunciation of “One”. Then, the extracted speech waveform is analyzed, and the pitch of speech and the utterance time of each word are calculated.

Next, the CPU 102 outputs the learner data stored in the storage unit 105 to the voice processing unit 108 (step SA15). Further, the CPU 102 controls the display unit 106 to display the selected example sentence and the pitch of the learner's voice obtained in step SA14 in the same manner as when the pitch of the model voice is displayed (step SA16). Here, the display length in the horizontal direction of each word and pitch of the example sentence is set to the same length as the display length when the pitch of the model voice is displayed.
In the displayed screen, the left end of the example sentence and the left end of the pitch display indicate the playback start time of the model voice, and the right end of the example sentence and the right end of the pitch display indicate the playback end time of the model sound.

  When learner data is input to the voice processing unit 108, the learner data that is digital data is converted into an analog signal and output to the speaker 110, and the learner's voice is reproduced from the speaker 110. When the learner's voice is reproduced, the CPU 102 controls the display unit 106 to display a bar indicating the portion of the displayed example sentence that is reproduced by voice (step SA17).

  Here, when the utterance time of the learner's “One” is the same as the utterance time of the model voice “One”, the CPU 102 sets the display interval of the pitch of “One” at the same speed as when the model voice is played back. The bar 10 is displayed to move. That is, if the learner's utterance time of “One” is 200 msec, which is the same as the utterance time of “One” of the model voice, the bar 10 moves over the display interval of the pitch of “One” over 200 msec. Is displayed. On the other hand, when the utterance time of the learner “One” is different from the utterance time of the model voice “One”, for example, 300 msec, the bar 10 sets the display interval of the pitch of “One” to 300 msec. Appears to move. That is, the speed of the bar 10 that moves in the “One” section on the display screen is slower than the moving speed of the bar 10 when the model voice is played back. It is possible to know that the utterance time of “One” is longer than the utterance time of “One” of the model voice. In addition, when the utterance time of the learner “One” is 100 msec shorter than, for example, the pronunciation of the model voice “One”, the bar 10 is moved so as to move over the display interval of the pitch of “One” over 100 msec. Is displayed. In other words, the speed of the bar 10 moving in the “One” section on the display screen is faster than the moving speed of the bar 10 when the model voice is played back. It is possible to know that the utterance time of “One” is shorter than the utterance time of “One” of the model voice.

  Similarly, the CPU 102 moves and displays the bar 10 according to the utterance time calculated in step SA14 for other words, and controls the display unit 106 when the learner's voice has been reproduced to pronounce the selected example sentence. A menu screen for confirming whether to practice again or to practice pronunciation of other example sentences is displayed (step SA18). When the learner operates the input unit 107 and performs an operation for practicing pronunciation of another example sentence (step SA19; YES), the CPU 102 returns the process flow to step SA1, and performs the processes after step SA1. Run again. When the learner operates the input unit 107 to perform the pronunciation practice of the selected example sentence again (step SA20; YES), the CPU 102 returns the process flow to step SA9, and after step SA9. The above process is executed again.

  As described above, according to the present embodiment, the dynamic change of the pronunciation rhythm in the model voice and the dynamic change of the pronunciation rhythm in the learner's voice are displayed. It is possible to grasp the difference in pronunciation rhythm between voice and model voice. And since it becomes possible to grasp the difference in pronunciation rhythm with the model voice, it becomes easy to bring the pronunciation close to the model voice.

[Modification]
As mentioned above, although embodiment of this invention was described, this invention is not limited to embodiment mentioned above, It can implement with other various forms as follows.

  In the above-described embodiment, when the bar indicating the playback position of the learner's voice is displayed, the bar indicating the playback position of the model voice may be displayed at the same time. According to such an aspect, it is possible to specifically know how early (slow) the pronunciation of the model voice is. Further, when the pitch of the learner's voice is displayed, the pitch of the model voice may be displayed so as to overlap as shown in FIG.

  In the embodiment described above, the language learning device 1 may store and reproduce example sentences and model voices in other languages as well as English such as French and German.

  In the embodiment described above, the pitch of the model voice and the learner's voice is displayed, but the pitch may not be displayed, and the bar 10 may be displayed on the displayed example sentence. Further, a time axis may be displayed instead of displaying the pitch.

In the above-described embodiment, the audio reproduction portion is represented by the bar 10, but the audio reproduction position is represented by changing the color of the reproduced portion to a color different from the color of the non-reproduced portion. You may do it.
In the above-described embodiment, the time interval of one frame is 100 msec, but the time interval of one frame may be other than 100 msec.
Further, in the above-described embodiment, when displaying an example sentence, a break is displayed for each word, but a break may be displayed for each phoneme.
In the above-described embodiment, the temporal change in voice power may be analyzed, and the temporal change in voice power analyzed instead of the pitch may be displayed.

  In the embodiment described above, the program executed by the CPU 102 may be stored in the storage unit 105, and the CPU 102 may read the program from the storage unit 105 and execute it. Alternatively, the language learning device 1 may have a communication function, and a program executed by the CPU 102 may be downloaded via a communication network and stored in the storage unit 105. Further, the language learning device 1 may read a program recorded on a recording medium such as a CD-ROM and store the read program in the storage unit 105.

It is a block diagram of the learning apparatus which concerns on embodiment of this invention. It is the figure which illustrated the format of example sentence table TB1. It is the figure which illustrated the format of pitch table TB2. It is the figure which illustrated the change of the pitch in model voice. It is the figure which illustrated the format of word table TB3. It is the flowchart which showed the flow of the process which CPU102 performs. 6 is a diagram illustrating a screen displayed on the display unit 106. FIG. It is the figure which illustrated the waveform of the model voice, and the waveform of the learner voice. It is a figure when the waveform of an exemplary voice and the waveform of a learner voice are divided into a plurality of frames. It is the figure which illustrated the screen display in a modification.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Language learning apparatus, 101 ... Bus, 102 ... CPU, 103 ... ROM, 104 ... RAM, 105 ... Memory | storage part, 106 ... Display part, 107 ... Input unit, 108... Voice processing unit, 109... Microphone, 110.

Claims (2)

Storage means for storing sound data corresponding to the sound to be pronounced divided into predetermined sections;
Reproduction means for reading out the sound data from the storage means and performing reproduction processing;
Sound collection data generating means for generating data corresponding to the collected sound as sound collection data;
A position adding means for recognizing a portion corresponding to the delimiter of the sound data with respect to the collected sound data and adding a corresponding delimiter;
Display means for displaying a scale formed by connecting display sections having a display width corresponding to the time length of each section;
First display control means for displaying the reproduction position in each section of the sound data for each display section of the scale in synchronization with the reproduction processing by the reproduction means;
Sound collection data reproduction processing means for reproducing the sound collection data;
Second display control means for displaying the reproduction position in each section of the collected sound data divided by the position adding means for each display section of the scale in synchronization with the collected sound data reproduction processing means. A reproducing apparatus. The storage means stores a plurality of different sound data,
Selecting means for selecting one of a plurality of sound data stored in the storage means;
The playback apparatus according to claim 1, wherein the playback means reads out the sound data selected by the selection means from the storage means and performs playback processing.

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