CN114613361A - Voice feedback and interaction system and method - Google Patents

Voice feedback and interaction system and method Download PDF

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CN114613361A
CN114613361A CN202210134308.XA CN202210134308A CN114613361A CN 114613361 A CN114613361 A CN 114613361A CN 202210134308 A CN202210134308 A CN 202210134308A CN 114613361 A CN114613361 A CN 114613361A
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voice
matching
value
point
target image
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CN114613361B (en
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张学军
李斌
韦依妮
张素素
陈婧娴
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Guangxi University
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/063—Training
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/063—Training
    • G10L2015/0631—Creating reference templates; Clustering
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
    • G10L2015/225—Feedback of the input speech

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Abstract

The invention relates to a voice feedback and interaction system and a method, which solve the technical problems of low efficiency and low accuracy, and the voice feedback and interaction system comprises the following components: the voice recognition device is connected with the voice acquisition device, and the voice feedback and interaction result output device is connected with the voice recognition device; the voice recognition device comprises a voice characteristic library storage unit and a processing unit, wherein the processing unit is used for establishing a historical statement voice characteristic diagram library, acquiring a target statement voice characteristic diagram of an interaction person in real time, acquiring an effective area of the target statement voice characteristic diagram, and then carrying out consistency comparison matching.

Description

Voice feedback and interaction system and method
Technical Field
The invention relates to the field of voice feedback and interaction, in particular to a voice feedback and interaction system and method.
Background
With the popularization of computer technology, people's lives have gradually entered the intelligent era nowadays. Not only computer, cell-phone, PAD, people's clothing and eating the square of walking all begin to use the intelligent technology that appears soon, smart television, intelligent navigation, intelligent house etc. and the intelligent technology will provide convenient and fast service in each aspect of people's life.
The intelligent voice interaction is a new generation interaction mode based on voice input, and a feedback result can be obtained by speaking. Typical application scenario-voice assistant. Since the introduction of SIRI from iPhone 4S, intelligent voice interactive applications have been rapidly developed. The typical intelligent voice interactive application in Chinese is as follows: wormhole voice assistants, news flying spots, have gained increasing user acceptance.
The existing voice feedback and interaction system and method have the problems of low efficiency and low precision. The invention provides a voice feedback and interaction system and a voice feedback and interaction method, which can solve the problem.
Disclosure of Invention
The invention aims to solve the technical problems of low efficiency and low precision in the prior art. The novel voice feedback and interaction system is provided, and has the characteristics of high efficiency and high precision.
In order to solve the technical problems, the technical scheme is as follows:
a voice feedback and interaction system, the voice feedback and interaction system comprising: the voice recognition device is connected with the voice acquisition device, and the voice feedback and interaction result output device is connected with the voice recognition device;
the voice recognition device comprises a voice characteristic database storage unit and a processing unit, wherein the processing unit executes the following steps:
step one, establishing a historical sentence voice feature map library, wherein the historical voice feature map is a sentence voice feature map drawn by extracting features of previously input or historically recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
secondly, extracting the characteristics of the sentence voice acquired by the voice acquisition device in real time, and drawing a target sentence voice characteristic diagram; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the retrieval matching step length to be L/2, sequentially performing retrieval matching along the x direction, not performing retrieval matching on the points which are retrieved and matched before, automatically reducing the retrieval matching step length by half when the retrieval matching exceeds the range, continuing the retrieval matching until the step length is reduced to the minimum, defining the new 1-value point which appears in the retrieval matching process as a new point which needs to be subjected to y-direction retrieval matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of retrieval matching is L/2 unchanged, retrieval matching is carried out in sequence along the y direction, points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, a new 1-value point which appears in the retrieval matching process is defined as a new point which needs to be retrieved and matched in the x direction, step five is executed, and otherwise, step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete interaction.
The working principle of the invention is as follows: the speech feature recognition in the present invention is the overall recognition of the diagnostic image, and can have higher recognition efficiency. Meanwhile, the part of the interactor not speaking is provided in the voice characteristic diagram acquired in the time sequence, so that the efficiency is improved.
To increase the accuracy, the eighth step further includes an image checking process, including:
step 1, defining effective target image as
Figure RE-GDA0003627415010000031
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure RE-GDA0003627415010000041
The relationship is as follows:
Figure RE-GDA0003627415010000042
wherein alpha iszIn order to be a scale-shift parameter,
Figure RE-GDA0003627415010000043
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure RE-GDA0003627415010000044
Figure RE-GDA0003627415010000045
Target image
Figure RE-GDA0003627415010000046
Projection in radial direction
Figure RE-GDA0003627415010000047
Will KC(i) And
Figure RE-GDA0003627415010000048
taking logarithm to obtain LKC(i) And
Figure RE-GDA0003627415010000049
will LKC(i) And
Figure RE-GDA00036274150100000410
as a scale deviation parameter alphaz；
Figure RE-GDA00036274150100000411
Figure RE-GDA00036274150100000412
Figure RE-GDA00036274150100000413
Figure RE-GDA00036274150100000414
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; size of the target image is 2Kmax× 2Kmax，nr＝KmaxNumber of samples taken in radial direction, nφ＝8KiThe number of samples in the angle direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure RE-GDA00036274150100000415
In the radial direction and angleProjection of (2):
Figure RE-GDA00036274150100000416
Figure RE-GDA00036274150100000417
to pair
Figure RE-GDA00036274150100000418
And
Figure RE-GDA00036274150100000419
carrying out normalized calculation to calculate the translation amount of the highest point
Figure RE-GDA00036274150100000420
According to
Figure RE-GDA0003627415010000051
Calculating a rotational offset parameter
Figure RE-GDA0003627415010000052
Step 5, rotating the offset parameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure RE-GDA0003627415010000053
Calculate ezPosition point corresponding to minimum value
Figure RE-GDA0003627415010000054
And finishing the image proofreading processing for the central point of the target image.
Further, the eight-step consistency matching identification further comprises:
step A, target image is processed
Figure RE-GDA0003627415010000055
Taking the central point as a center to make a concentric circle, dividing the fingerprint image into B annular areas, and finally dividing each annular area into K fan-shaped areas, wherein K and B are predefined constants;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Code 1;
Figure RE-GDA0003627415010000056
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθRepresenting a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped area SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after the fingerprint image is rotated (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical statement voice feature gallery for matching.
The invention also provides a voice feedback and interaction method, which is based on the voice feedback and interaction system, and comprises the following steps:
step one, a voice interactor outputs real-time sentence voice, and a voice acquisition device acquires the real-time sentence voice of the interactor; drawing a target sentence voice feature graph; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step two, the processing unit calls a preset historical sentence voice feature map library stored in the storage unit, the historical voice feature map is a sentence voice feature map drawn by extracting features of previously input or historical recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the retrieval matching step length to be L/2, sequentially performing retrieval matching along the x direction, not performing retrieval matching on the points which are retrieved and matched before, automatically reducing the retrieval matching step length by half when the retrieval matching exceeds the range, continuing the retrieval matching until the step length is reduced to the minimum, defining the new 1-value point which appears in the retrieval matching process as a new point which needs to be subjected to y-direction retrieval matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of the retrieval matching is unchanged at L/2, the retrieval matching is sequentially carried out along the y direction, the points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, and if a new 1-value point appears in the retrieval matching process, the new point which needs to be retrieved and matched in the x direction is defined as a new point, the step five is executed, otherwise, the step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete voice interaction and feedback.
Further, the eighth step further includes an image collation process including:
step 1, defining effective target image as
Figure RE-GDA0003627415010000071
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure RE-GDA0003627415010000072
The relationship is as follows:
Figure RE-GDA0003627415010000073
wherein alpha iszIn order to be a scale-shift parameter,
Figure RE-GDA0003627415010000074
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure RE-GDA0003627415010000075
Figure RE-GDA0003627415010000076
Target image
Figure RE-GDA0003627415010000077
Projection in radial direction
Figure RE-GDA0003627415010000078
Will KC(i) And
Figure RE-GDA0003627415010000079
taking logarithm to obtain LKC(i) And
Figure RE-GDA00036274150100000710
will LKC(i) And
Figure RE-GDA00036274150100000711
as a scale deviation parameter alphaz；
Figure RE-GDA0003627415010000081
Figure RE-GDA0003627415010000082
Figure RE-GDA0003627415010000083
Figure RE-GDA0003627415010000084
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; size of the target image is 2Kmax× 2Kmax，nr＝KmaxNumber of samples in radial direction, nφ＝8KiThe number of samples in the angle direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure RE-GDA0003627415010000085
Projection in radial and angular directions:
Figure RE-GDA0003627415010000086
Figure RE-GDA0003627415010000087
to pair
Figure RE-GDA0003627415010000088
And
Figure RE-GDA0003627415010000089
carrying out normalized calculation to calculate the translation amount of the highest point
Figure RE-GDA00036274150100000810
According to
Figure RE-GDA00036274150100000811
Calculating a rotational offset parameter
Figure RE-GDA00036274150100000812
Step 5, rotating the offset parameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure RE-GDA00036274150100000813
Calculate ezPosition point corresponding to minimum value
Figure RE-GDA00036274150100000814
And finishing the image proofreading processing for the central point of the target image.
Further, the eight-step consistency matching identification further comprises:
step A, target image is processed
Figure RE-GDA00036274150100000815
Taking the central point as a center to make a concentric circle, dividing the fingerprint image into B annular areas, and finally dividing each annular area into K fan-shaped areas, wherein K and B are predefined constants;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Code 1;
Figure RE-GDA0003627415010000091
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθIndicates a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped area SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after rotating the fingerprint image (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical statement voice feature gallery for matching.
The invention has the beneficial effects that: the invention converts the speech feature recognition into the integral recognition of the feature map, and has higher recognition efficiency. Meanwhile, the part of the interactor not speaking is provided in the voice characteristic diagram acquired in the time sequence, so that the efficiency is improved. In addition, the accuracy of feedback and interaction is improved through pre-intersection proofreading and positioning processing of the characteristic images.
Drawings
The invention is further illustrated by the following examples in conjunction with the drawings.
FIG. 1, a schematic diagram of a voice feedback and interaction system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
The present embodiment provides a voice feedback and interaction system, as shown in fig. 1, the voice feedback and interaction system includes: the voice recognition device is connected with the voice acquisition device, and the voice feedback and interaction result output device is connected with the voice recognition device;
the voice recognition device comprises a voice characteristic database storage unit and a processing unit, wherein the processing unit executes the following steps:
step one, establishing a historical sentence voice feature map library, wherein the historical voice feature map is a sentence voice feature map drawn by extracting features of previously input or historically recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
secondly, extracting the characteristics of the sentence voice acquired by the voice acquisition device in real time, and drawing a target sentence voice characteristic diagram; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the retrieval matching step length to be L/2, sequentially performing retrieval matching along the x direction, not performing retrieval matching on the points which are retrieved and matched before, automatically reducing the retrieval matching step length by half when the retrieval matching exceeds the range, continuing the retrieval matching until the step length is reduced to the minimum, defining the new 1-value point which appears in the retrieval matching process as a new point which needs to be subjected to y-direction retrieval matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of retrieval matching is L/2 unchanged, retrieval matching is carried out in sequence along the y direction, points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, a new 1-value point which appears in the retrieval matching process is defined as a new point which needs to be retrieved and matched in the x direction, step five is executed, and otherwise, step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete interaction.
The working principle of the invention is as follows: the speech feature recognition in the present invention is the overall recognition of the diagnostic image, and can have higher recognition efficiency. Meanwhile, the part of the interactor not speaking is provided in the voice characteristic diagram acquired in the time sequence, so that the efficiency is improved.
To increase the accuracy, preferably, the eighth step further includes an image checking process including:
step 1, defining effective target image as
Figure RE-GDA0003627415010000111
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure RE-GDA0003627415010000121
The relationship is as follows:
Figure RE-GDA0003627415010000122
wherein the content of the first and second substances,αzin order to be a scale-shift parameter,
Figure RE-GDA0003627415010000123
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure RE-GDA0003627415010000124
Figure RE-GDA0003627415010000125
Target image
Figure RE-GDA0003627415010000126
Projection in radial direction
Figure RE-GDA0003627415010000127
Will KC(i) And
Figure RE-GDA0003627415010000128
taking logarithm to obtain LKC(i) And
Figure RE-GDA0003627415010000129
LK is to beC(i) And
Figure RE-GDA00036274150100001210
as a scale deviation parameter alphaz；
Figure RE-GDA00036274150100001211
Figure RE-GDA00036274150100001212
Figure RE-GDA00036274150100001213
Figure RE-GDA00036274150100001214
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; size of the target image is 2Kmax× 2Kmax，nr＝KmaxNumber of samples taken in radial direction, nφ＝8KiThe number of samples taken in the angular direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure RE-GDA00036274150100001215
Projection in radial and angular directions:
Figure RE-GDA00036274150100001216
Figure RE-GDA00036274150100001217
to pair
Figure RE-GDA0003627415010000131
And
Figure RE-GDA0003627415010000132
carrying out normalized calculation to calculate the translation amount of the highest point
Figure RE-GDA0003627415010000133
According to
Figure RE-GDA0003627415010000134
Calculating a rotational offset parameter
Figure RE-GDA0003627415010000135
Step 5, offsetting the rotationParameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure RE-GDA0003627415010000136
Calculate ezPosition point corresponding to minimum value
Figure RE-GDA0003627415010000137
And finishing the image proofreading processing for the central point of the target image.
Preferably, the eight-consistency matching identification step further comprises:
step A, target image is processed
Figure RE-GDA0003627415010000138
Taking the central point as a center to make a concentric circle, dividing the fingerprint image into B annular areas, and finally dividing each annular area into K fan-shaped areas, wherein K and B are predefined constants;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Code 1;
Figure RE-GDA0003627415010000139
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθRepresenting a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped area SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after rotating the fingerprint image (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical statement voice feature gallery for matching.
The embodiment also provides a voice feedback and interaction method, which is based on the voice feedback and interaction system, and the voice feedback and interaction method includes:
step one, a voice interactor outputs real-time sentence voice, and a voice acquisition device acquires the real-time sentence voice of the interactor; drawing a target sentence voice feature graph; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step two, the processing unit calls a preset historical sentence voice feature map library stored in the storage unit, the historical voice feature map is a sentence voice feature map drawn by extracting features of previously input or historical recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the retrieval matching step length to be L/2, sequentially performing retrieval matching along the x direction, not performing retrieval matching on the points which are retrieved and matched before, automatically reducing the retrieval matching step length by half when the retrieval matching exceeds the range, continuing the retrieval matching until the step length is reduced to the minimum, defining the new 1-value point which appears in the retrieval matching process as a new point which needs to be subjected to y-direction retrieval matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of retrieval matching is L/2 unchanged, retrieval matching is carried out in sequence along the y direction, points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, a new 1-value point which appears in the retrieval matching process is defined as a new point which needs to be retrieved and matched in the x direction, step five is executed, and otherwise, step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete voice interaction and feedback.
Preferably, the eighth step further includes an image collation process including:
step 1, defining effective target image as
Figure RE-GDA0003627415010000151
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure RE-GDA0003627415010000152
The relationship is as follows:
Figure RE-GDA0003627415010000153
wherein alpha iszIn order to be a scale-shift parameter,
Figure RE-GDA0003627415010000154
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure RE-GDA0003627415010000155
Figure RE-GDA0003627415010000156
Target image
Figure RE-GDA0003627415010000157
Projection in radial direction
Figure RE-GDA0003627415010000158
Will KC(i) And
Figure RE-GDA0003627415010000161
taking logarithm to obtain LKC(i) And
Figure RE-GDA0003627415010000162
will LKC(i) And
Figure RE-GDA0003627415010000163
as a scale deviation parameter alphaz；
Figure RE-GDA0003627415010000164
Figure RE-GDA0003627415010000165
Figure RE-GDA0003627415010000166
Figure RE-GDA0003627415010000167
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; eyes of a userThe size of the target image is 2Kmax× 2Kmax，nr＝KmaxNumber of samples taken in radial direction, nφ＝8KiThe number of samples in the angle direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure RE-GDA0003627415010000168
Projection in radial and angular directions:
Figure RE-GDA0003627415010000169
Figure RE-GDA00036274150100001610
to pair
Figure RE-GDA00036274150100001611
And
Figure RE-GDA00036274150100001612
carrying out normalization calculation to calculate the translation amount of the highest point
Figure RE-GDA00036274150100001613
According to
Figure RE-GDA00036274150100001614
Calculating a rotational offset parameter
Figure RE-GDA00036274150100001615
Step 5, rotating the offset parameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure RE-GDA00036274150100001616
Calculate ezPosition point corresponding to minimum value
Figure RE-GDA00036274150100001617
And finishing the image proofreading processing for the central point of the target image.
Preferably, the eight-consistency matching identification step further comprises:
step A, target image is processed
Figure RE-GDA00036274150100001618
Taking the central point as a center to make a concentric circle, dividing the fingerprint image into B annular areas, and finally dividing each annular area into K fan-shaped areas, wherein K and B are predefined constants;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Code 1;
Figure RE-GDA0003627415010000171
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθIndicates a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped area SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after rotating the fingerprint image (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical statement voice feature gallery for matching.
The feature recognition of the speech in this embodiment is the overall recognition of the diagnostic graph, and can have higher recognition efficiency. Meanwhile, the part of the interactor not speaking is provided in the voice characteristic diagram acquired in the time sequence, so that the efficiency is improved. Meanwhile, the accuracy of feedback and interaction is improved by pre-intersection proofreading and positioning processing of the characteristic images.
Although the illustrative embodiments of the present invention have been described above to enable those skilled in the art to understand the present invention, the present invention is not limited to the scope of the embodiments, and it is apparent to those skilled in the art that all the inventive concepts using the present invention are protected as long as they can be changed within the spirit and scope of the present invention as defined and defined by the appended claims.

Claims (6)

1. A voice feedback and interaction system, characterized by: the voice feedback and interaction system comprises: the voice recognition device is connected with the voice acquisition device, and the voice feedback and interaction result output device is connected with the voice recognition device;
the voice recognition device comprises a voice characteristic database storage unit and a processing unit, wherein the processing unit executes the following steps:
step one, establishing a historical sentence voice feature map library, wherein the historical voice feature map is a sentence voice feature map drawn by extracting features of previously input or historically recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
step two, performing feature extraction on the sentence voice acquired by the voice acquisition device in real time, and drawing a target sentence voice feature map; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the retrieval matching step length to be L/2, sequentially performing retrieval matching along the x direction, not performing retrieval matching on the points which are retrieved and matched before, automatically reducing the retrieval matching step length by half when the retrieval matching exceeds the range, continuing the retrieval matching until the step length is reduced to the minimum, defining the new 1-value point which appears in the retrieval matching process as a new point which needs to be subjected to y-direction retrieval matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of retrieval matching is L/2 unchanged, retrieval matching is carried out in sequence along the y direction, points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, a new 1-value point which appears in the retrieval matching process is defined as a new point which needs to be retrieved and matched in the x direction, step five is executed, and otherwise, step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete interaction.
2. The voice feedback and interaction system of claim 1, wherein: the eighth step further includes an image collation process including:
step 1, defining effective target image as
Figure FDA0003503784770000021
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure FDA0003503784770000022
The relationship is as follows:
Figure FDA0003503784770000023
wherein alpha iszIn order to be a scale-shift parameter,
Figure FDA0003503784770000024
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure FDA0003503784770000031
Figure FDA0003503784770000032
Target image
Figure FDA0003503784770000033
Projection in radial direction
Figure FDA0003503784770000034
Will KC(i) And
Figure FDA0003503784770000035
taking logarithm to obtain LKC(i) And
Figure FDA0003503784770000036
will LKC(i) And
Figure FDA0003503784770000037
as a scale deviation parameter alphaz；
Figure FDA0003503784770000038
Figure FDA0003503784770000039
Figure FDA00035037847700000310
Figure FDA00035037847700000311
Figure FDA00035037847700000312
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; size of the target image is 2Kmax×2Kmax，nr＝KmaxNumber of samples taken in radial direction, nφ＝8KiThe number of samples in the angle direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure FDA00035037847700000313
Projection in radial and angular directions:
Figure FDA00035037847700000314
Figure FDA00035037847700000315
for is to
Figure FDA00035037847700000316
And
Figure FDA00035037847700000317
carrying out normalized calculation to calculate the translation amount of the highest point
Figure FDA00035037847700000318
According to
Figure FDA00035037847700000319
Figure FDA00035037847700000320
Calculating a rotational offset parameter
Figure FDA00035037847700000321
Step 5, rotating the offset parameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure FDA0003503784770000041
Calculate ezPosition point corresponding to minimum value
Figure FDA0003503784770000042
And finishing the image proofreading processing for the central point of the target image.
3. The voice feedback and interaction system of claim 1, wherein: the eight-consistency matching identification step further comprises:
step A, target image is processed
Figure FDA0003503784770000043
Using the central point as the center to make concentric circle, dividing the fingerprint image into B annular regions, and finally dividing each annular region into K fan-shaped regions, where K and B are both presetA constant of sense;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Codel;
Figure FDA0003503784770000044
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθRepresenting a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped area SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after rotating the fingerprint image (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical statement voice feature gallery for matching.
4. A voice feedback and interaction method, characterized by: the voice feedback and interaction method is based on the voice feedback and interaction system of any one of claims 1 to 3, and the voice feedback and interaction method comprises the following steps:
step one, a voice interactor outputs real-time sentence voice, and a voice acquisition device acquires the real-time sentence voice of the interactor; drawing a target sentence voice feature graph; the sentence voice feature map in the optional historical sentence voice feature map library is defined as a reference image, the target sentence voice feature map is defined as a target image,
step two, the processing unit calls a preset historical sentence voice feature map library stored in the storage unit, the historical voice feature map is a sentence voice feature map which is drawn by extracting features of the pre-input or historical recorded sentence voice, and the sentence voice feature map comprises character, word and sentence feature maps;
step three, the target image ICCarrying out binarization processing, wherein a value of 1 is defined as having voice characteristics, and a value of 0 is defined as having no voice characteristics; dividing the feature map after binarization processing into a grid map by adopting a unit grid, defining the initial point (x1, y1) of the grid map as an origin, defining the search matching step length as L, searching along the direction of x from the origin, recording the position and the value of the point if the searched value is 1, labeling in sequence, otherwise, continuing to search for matching;
step four, updating the point (x1, y1+ N L) as an original point, returning to execute the step three until the retrieval and matching in the x direction and the y direction are finished, and finishing the preliminary positioning retrieval and matching, wherein N is an integer, and L is a constant;
step five, sequentially taking out the points with the value of 1, updating the 1-value point taken out at the current time to the original point, updating the search matching step length to be L/2, sequentially performing search matching along the x direction, not performing search matching on the points which are searched and matched before, automatically halving the search matching step length when the search matching exceeds the range, continuing search matching until the step length is minimized, defining the new 1-value point in the search matching process as a new point which needs to be subjected to y-direction search matching, and executing the step six, otherwise, executing the step seven;
step six, the step length of retrieval matching is L/2 unchanged, retrieval matching is carried out in sequence along the y direction, points which are retrieved and matched before are not retrieved and matched, if the retrieval matching exceeds the range, the step length of the retrieval matching is automatically halved, the retrieval matching is continued until the step length is minimized, a new 1-value point which appears in the retrieval matching process is defined as a new point which needs to be retrieved and matched in the x direction, step five is executed, and otherwise, step seven is executed;
step seven, until no new point needs to be searched and matched, ending the search and matching, and collecting the areas of the searched and matched 1-value points as an effective target image;
step eight, carrying out consistency matching identification on the effective target image in a historical sentence voice feature gallery;
and step nine, outputting the recognition result through a voice feedback and interaction result output device to complete voice interaction and feedback.
5. The voice feedback and interaction method of claim 4, wherein: the eighth step further includes an image collation process including:
step 1, defining effective target image as
Figure FDA0003503784770000061
Defining a reference image in the speech feature map library of the optional historical statement as IC；
Step 2, defining a reference image ICAnd the target image after polar coordinate transformation
Figure FDA0003503784770000062
The relationship is as follows:
Figure FDA0003503784770000063
wherein alpha iszIn order to be a scale-shift parameter,
Figure FDA0003503784770000064
is a rotational offset parameter;
step 3, calculating a reference image ICProjection in radial direction in polar coordinate system
Figure FDA0003503784770000065
Figure FDA0003503784770000066
Target image
Figure FDA0003503784770000067
Projection in radial direction
Figure FDA0003503784770000068
Will KC(i) And
Figure FDA0003503784770000069
taking logarithm to obtain LKC(i) And
Figure FDA00035037847700000610
will LKC(i) And
Figure FDA00035037847700000611
as a scale deviation parameter alphaz；
Figure FDA0003503784770000071
Figure FDA0003503784770000072
Figure FDA0003503784770000073
Figure FDA0003503784770000074
Figure FDA0003503784770000075
Is Ki＝KmaxThe number of samples in the angular direction, ce () representing the smallest integer greater than or equal to the value in parentheses, fl () representing the largest integer less than or greater than the value in parentheses; size of the target image is 2Kmax×2Kmax，nr＝KmaxNumber of samples taken in radial direction, nφ＝8KiThe number of samples in the angle direction;
step 4, calculating a reference image I according to the scale deviation parameters in the step 3CAnd a target image
Figure FDA0003503784770000076
Projection in radial and angular directions:
Figure FDA0003503784770000077
Figure FDA0003503784770000078
to pair
Figure FDA0003503784770000079
And
Figure FDA00035037847700000710
carrying out normalized calculation to calculate the translation amount of the highest point
Figure FDA00035037847700000711
According to
Figure FDA00035037847700000712
Figure FDA00035037847700000713
Calculating a rotational offset parameter
Figure FDA00035037847700000714
Step 5, rotating the offset parameter phizAnd a scale shift parameter αzCarrying out correction on the target image according to the step A
Figure FDA00035037847700000715
Calculate ezPosition point corresponding to minimum value
Figure FDA00035037847700000716
And finishing the image proofreading processing for the central point of the target image.
6. The voice feedback and interaction method of claim 4, wherein: the eight-consistency matching identification step further comprises:
step A, target image is processed
Figure FDA0003503784770000081
Taking the central point as a center to make a concentric circle, dividing the fingerprint image into B annular areas, and finally dividing each annular area into K fan-shaped areas, wherein K and B are predefined constants;
step B, calculating each sector SsqSector fingerprint feature value VsqθAs Code 1;
Figure FDA0003503784770000082
wherein, Fsqθ(x, y) is a sector area SsqOf each pixel, PsqθRepresenting a sector area SsqAverage value of inner pixel gray values, nsqIs a ring-shaped region SsqThe number of columns, 0 < sq ≦ bxk-1, {0 °, (360 °/K), 2 ° (360 °/K), 3 ° (360 °/K),. or.. ≦ 180 ° };
step C, after rotating the fingerprint image (180 degrees/K), repeating the step B, and extracting each sector SsqSector fingerprint feature value VsqθAs Code 2;
step E, respectively rotating Code1 and Code2 by R × (360 °/K) (R ═ 0,1,2.. K-1) to obtain Code1 'and Code 2';
and F, inputting the Code1 and the Code2, and the Code1 'and the Code 2' in the step E into a historical sentence voice feature gallery for matching.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11657803B1 (en) 2022-11-02 2023-05-23 Actionpower Corp. Method for speech recognition by using feedback information

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08314494A (en) * 1995-05-19 1996-11-29 Matsushita Electric Ind Co Ltd Information retrieving device
CN104505091A (en) * 2014-12-26 2015-04-08 湖南华凯文化创意股份有限公司 Human-machine voice interaction method and human-machine voice interaction system
CN107133612A (en) * 2017-06-06 2017-09-05 河海大学常州校区 Based on image procossing and the intelligent ward of speech recognition technology and its operation method
CN108073875A (en) * 2016-11-14 2018-05-25 广东技术师范学院 A kind of band noisy speech identifying system and method based on monocular cam

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08314494A (en) * 1995-05-19 1996-11-29 Matsushita Electric Ind Co Ltd Information retrieving device
CN104505091A (en) * 2014-12-26 2015-04-08 湖南华凯文化创意股份有限公司 Human-machine voice interaction method and human-machine voice interaction system
CN108073875A (en) * 2016-11-14 2018-05-25 广东技术师范学院 A kind of band noisy speech identifying system and method based on monocular cam
CN107133612A (en) * 2017-06-06 2017-09-05 河海大学常州校区 Based on image procossing and the intelligent ward of speech recognition technology and its operation method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
仲琛;肖南峰;: "指纹和声音自动识别系统的设计与实现", 计算技术与自动化, no. 02, 30 June 2006 (2006-06-30) *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11657803B1 (en) 2022-11-02 2023-05-23 Actionpower Corp. Method for speech recognition by using feedback information

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