CN113160828A - Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium - Google Patents
Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113160828A CN113160828A CN202110425094.7A CN202110425094A CN113160828A CN 113160828 A CN113160828 A CN 113160828A CN 202110425094 A CN202110425094 A CN 202110425094A CN 113160828 A CN113160828 A CN 113160828A
- Authority
- CN
- China
- Prior art keywords
- information
- voice
- intelligent auxiliary
- auxiliary robot
- intelligent
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 230000003993 interaction Effects 0.000 title claims abstract description 37
- 238000003058 natural language processing Methods 0.000 claims abstract description 17
- 238000006243 chemical reaction Methods 0.000 claims abstract description 10
- 238000000605 extraction Methods 0.000 claims abstract description 10
- 239000000284 extract Substances 0.000 claims abstract description 4
- 239000013598 vector Substances 0.000 claims description 10
- 230000007246 mechanism Effects 0.000 claims description 5
- 230000006870 function Effects 0.000 claims description 4
- 230000002452 interceptive effect Effects 0.000 claims description 4
- 230000004913 activation Effects 0.000 claims description 3
- 238000004590 computer program Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000009432 framing Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 7
- 230000003287 optical effect Effects 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000000474 nursing effect Effects 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 235000019800 disodium phosphate Nutrition 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000013136 deep learning model Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008451 emotion Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
Images
Classifications
-
- 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
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
-
- 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
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
- G10L19/16—Vocoder architecture
Landscapes
- Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Artificial Intelligence (AREA)
- Machine Translation (AREA)
Abstract
The invention provides an intelligent auxiliary robot interaction method, an intelligent auxiliary robot interaction system, electronic equipment and a storage medium. The method comprises the following steps: the intelligent auxiliary robot receives voice information of a user; the intelligent auxiliary robot carries out automatic voice recognition according to the received voice information to obtain corresponding character information; the intelligent auxiliary robot carries out natural language processing on the character information and converts the character information into a structured language; according to the structured language, the intelligent auxiliary robot extracts answer text information from a preset database; and the intelligent auxiliary robot converts the answer text information into voice and plays the voice from the sound equipment of the intelligent auxiliary robot. The system comprises: the device comprises a receiving module, a voice recognition module, a natural language processing module, a text extraction module and a voice conversion playing module. The method reduces the complexity in the process, and is simple and high in efficiency.
Description
Technical Field
The invention belongs to the technical field of robot voice interaction, and particularly relates to an intelligent auxiliary robot interaction method, an intelligent auxiliary robot interaction system, electronic equipment and a storage medium.
Background
China already enters an aging society, more and more products for nursing and accompanying the aged enter the market, wherein in recent years, robot products for nursing and accompanying the aged are more and more concerned by people. An intelligent auxiliary robot interaction method for old-age care and accompanying nursing is needed at present. Therefore, the intelligent assistant robot interaction method for the aged care and accompanying is designed for enriching the algorithm research in the related field.
Currently, for example, patent application No. cn112562685.a provides a voice interaction method and apparatus for a service robot, patent application CN202011210092.8 provides an emotion accompanying intelligent robot based on an intelligent interaction system, and patent application CN202011190277.7 provides a voice interaction processing method and robot for a robot. It can be seen from the above patent applications that most of the interaction methods have complicated processes and strong coupling, and the convenience of the whole interaction process needs to be further improved. Aiming at the problems of poor service experience and complex algorithm in the interaction process between a robot and a user, an intelligent auxiliary robot interaction method, a system, electronic equipment and a storage medium are designed.
Disclosure of Invention
Based on the technical defects, the application provides an intelligent auxiliary robot interaction method, an intelligent auxiliary robot interaction system, electronic equipment and a storage medium.
In a first aspect, the present application provides an intelligent auxiliary robot interaction method, including the following steps:
the intelligent auxiliary robot receives voice information of a user;
the intelligent auxiliary robot carries out automatic voice recognition according to the received voice information to obtain corresponding character information;
the intelligent auxiliary robot carries out natural language processing on the character information and converts the character information into a structured language;
according to the structured language, the intelligent auxiliary robot extracts answer text information from a preset database;
and the intelligent auxiliary robot converts the answer text information into voice and plays the voice from the sound equipment of the intelligent auxiliary robot.
The intelligent auxiliary robot receives voice information of a user, and comprises: and when the received voice information contains the set activation word information, the intelligent auxiliary robot starts the interactive function.
The automatic voice recognition, namely the audio data processing is carried out on the collected voice information, and the method comprises the following steps:
respectively carrying out filtering processing and framing processing on the voice information;
aiming at the processed voice information, converting the time domain information into frequency domain information, and converting each frame of waveform into a multi-dimensional feature vector;
calculating a score of each of the feature vectors over the acoustic features based on the acoustic characteristics;
calculating the probability of the possible phrase sequences corresponding to the voice information according to a linguistic model;
and finally, decoding the phrase sequence according to the existing dictionary to obtain corresponding character information.
The intelligent auxiliary robot converts the answer text information into voice, and the method comprises the following steps:
presetting voice print information of the intelligent auxiliary robot;
coding the corresponding character information, and splicing the character information by combining the voiceprint information;
decoding through the attention mechanism model to obtain decoding information;
outputting the decoded information to a vocoder of the intelligent auxiliary robot;
the vocoder generates a sound waveform from the decoded information.
In a second aspect, the present application provides an intelligent auxiliary robot interaction system, including:
the system comprises a receiving module, a voice recognition module, a natural language processing module, a text extraction module and a voice conversion playing module;
the receiving module, the voice recognition module, the natural language processing module, the text extraction module and the voice conversion playing module are sequentially connected;
the receiving module is used for receiving voice information of a user;
the voice recognition module is used for carrying out automatic voice recognition according to the received voice information to obtain corresponding character information;
the natural language processing module is used for carrying out natural language processing on the character information and converting the character information into a structured language;
the text extraction module is used for extracting answer text information from a preset database by the intelligent auxiliary robot according to the structured language;
and the voice conversion playing module is used for converting the answer text information into voice and playing the voice from the sound equipment of the intelligent auxiliary robot.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors for the intelligent auxiliary robot interaction method of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the intelligent assisted robot interaction method according to the first aspect or any one of the possible implementations of the first aspect.
The beneficial technical effects are as follows:
compared with the prior art, the invention has the advantages that: the interactive algorithm further optimizes the voice processing process, reduces the complexity in the process, and has the advantages of simplicity and high efficiency.
Drawings
Fig. 1 is a schematic diagram of an intelligent auxiliary robot interaction method according to an embodiment of the present application;
FIG. 2 is a schematic block diagram of an intelligent assistant robot interaction system according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
The invention will be described in further detail below with reference to the drawings and examples.
The application provides an intelligent auxiliary robot interaction method, an intelligent auxiliary robot interaction system, electronic equipment and a storage medium.
In a first aspect, the present application provides an intelligent auxiliary robot interaction method, as shown in fig. 1, including the following steps:
step S1: the intelligent auxiliary robot receives voice information of a user;
step S2: the intelligent auxiliary robot carries out automatic voice recognition according to the received voice information to obtain corresponding character information;
and the automatic voice recognition is used for analyzing the acoustic voice to obtain corresponding text information.
Step S3: the intelligent auxiliary robot carries out natural language processing on the character information and converts the character information into a structured language;
step S4: according to the structured language, the intelligent auxiliary robot extracts answer text information from a preset database;
step S5: and the intelligent auxiliary robot converts the answer text information into voice and plays the voice from the sound equipment of the intelligent auxiliary robot.
The intelligent auxiliary robot receives voice information of a user, and comprises: and when the received voice information contains the set activation word information, the intelligent auxiliary robot starts the interactive function.
The automatic voice recognition, namely the audio data processing is carried out on the collected voice information, and the method comprises the following steps:
respectively carrying out filtering processing and framing processing on the voice information;
aiming at the processed voice information, converting the time domain information into frequency domain information, and converting each frame of waveform into a multi-dimensional feature vector;
calculating a score of each of the feature vectors over the acoustic features based on the acoustic characteristics;
calculating the probability of the possible phrase sequences corresponding to the voice information according to a linguistic model;
the phonetic model includes many classical models, which belong to the scope of protection in the present application, and the phonetic model used in the present embodiment is a classical Hidden Markov Model (HMM) using the speech recognition field. In speech recognition, hidden markov models are used to model acoustic observations (feature vectors) of subword levels (e.g., english phonemes). Typically 3 states are modeled for each phoneme, modeling the beginning, middle and end of the phoneme, respectively.
The hidden Markov model models the recognition primitive from left to right with a one-way, self-looping, spanning topology, one phoneme is a three-state HMM, one word is an HMM formed by connecting HMMs of a plurality of phonemes forming the word in series, and the whole model of continuous speech recognition is an HMM formed by combining the word and silence.
And finally, decoding the phrase sequence according to the existing dictionary to obtain corresponding character information.
The intelligent auxiliary robot converts the answer text information into voice, and the method comprises the following steps:
presetting voice print information of the intelligent auxiliary robot;
coding the corresponding character information, and splicing the character information by combining the voiceprint information; the splicing treatment specifically comprises the following steps: and according to the sequence of each word in each sentence, the voiceprint information of the words is trained into the voiceprint of the whole sentence.
Decoding through the attention mechanism model to obtain decoding information;
in the present application, attention model, all modifications of attention model and variations of attention model are within the scope of the present application.
The attention mechanism model adopted by the embodiment is a technology for extracting effective features from a feature sequence in a sequence-to-sequence model. As a classic process sequence data deep learning model. The characteristic sequence and the intermediate sequence are defined in the model calculation. When decoding, firstly, the encoder neural network preprocesses the input features, encodes the feature sequences into vector sequences which are easier to classify, then sends the vector sequences into a decoder, obtains output probability vectors by combining historical decoding output of the decoder neural network, and can obtain output characters of the text corresponding to the dimensionality with the maximum probability. To deal with the problem of length mismatch of the encoder output and the decoder output, an attention mechanism may be used.
Outputting the decoded information to a vocoder of the intelligent auxiliary robot;
the vocoder generates a sound waveform from the decoded information.
In a second aspect, the present application provides an intelligent auxiliary robot interaction system, as shown in fig. 2, including:
the system comprises a receiving module, a voice recognition module, a natural language processing module, a text extraction module and a voice conversion playing module;
the receiving module, the voice recognition module, the natural language processing module, the text extraction module and the voice conversion playing module are sequentially connected;
the receiving module is used for receiving voice information of a user;
the voice recognition module is used for carrying out automatic voice recognition according to the received voice information to obtain corresponding character information;
the natural language processing module is used for carrying out natural language processing on the character information and converting the character information into a structured language;
the text extraction module is used for extracting answer text information from a preset database by the intelligent auxiliary robot according to the structured language;
and the voice conversion playing module is used for converting the answer text information into voice and playing the voice from the sound equipment of the intelligent auxiliary robot.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors for the intelligent auxiliary robot interaction method of the first aspect.
As shown in fig. 3, the electronic apparatus 100 includes: a processor 101 and a memory 103. Wherein the processor 101 is coupled to the memory 103, such as via a bus 102.
The structure of the electronic device 100 is not limited to the embodiment of the present application.
The processor 101 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 101 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors.
The memory 103 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the intelligent assisted robot interaction method according to the first aspect or any one of the possible implementations of the first aspect.
It will be understood by those skilled in the art that all or part of the steps of the above methods may be implemented by instructing the relevant hardware through a program, and the program may be stored in a computer readable storage medium, such as a read-only memory, a magnetic or optical disk, and the like. Alternatively, all or part of the steps of the foregoing embodiments may also be implemented by using one or more integrated circuits, and accordingly, each module/unit in the foregoing embodiments may be implemented in the form of hardware, and may also be implemented in the form of a software functional module. The present invention is not limited to any specific form of combination of hardware and software.
It should be noted that the present invention can be embodied in other specific forms, and various changes and modifications can be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (7)
1. An intelligent auxiliary robot interaction method is characterized by comprising the following steps:
the intelligent auxiliary robot receives voice information of a user;
the intelligent auxiliary robot carries out automatic voice recognition according to the received voice information to obtain corresponding character information;
the intelligent auxiliary robot carries out natural language processing on the character information and converts the character information into a structured language;
according to the structured language, the intelligent auxiliary robot extracts answer text information from a preset database;
and the intelligent auxiliary robot converts the answer text information into voice and plays the voice from the sound equipment of the intelligent auxiliary robot.
2. The intelligent assisted robot interaction method of claim 1, wherein the intelligent assisted robot receives voice information of a user, comprising: and when the received voice information contains the set activation word information, the intelligent auxiliary robot starts the interactive function.
3. The intelligent assistant robot interaction method according to claim 1, wherein the automatic speech recognition, i.e. the audio data processing of the collected speech information, comprises the following steps:
respectively carrying out filtering processing and framing processing on the voice information;
aiming at the processed voice information, converting the time domain information into frequency domain information, and converting each frame of waveform into a multi-dimensional feature vector;
calculating a score of each of the feature vectors over the acoustic features based on the acoustic characteristics;
calculating the probability of the possible phrase sequences corresponding to the voice information according to a linguistic model;
and finally, decoding the phrase sequence according to the existing dictionary to obtain corresponding character information.
4. The intelligent assisted robot interaction method of claim 1, wherein the intelligent assisted robot converts the answer text information into voice, comprising the steps of:
presetting voice print information of the intelligent auxiliary robot;
coding the corresponding character information, and splicing the character information by combining the voiceprint information;
decoding through the attention mechanism model to obtain decoding information;
outputting the decoded information to a vocoder of the intelligent auxiliary robot;
the vocoder generates a sound waveform from the decoded information.
5. An intelligent assisted robot interaction system, comprising: the system comprises a receiving module, a voice recognition module, a natural language processing module, a text extraction module and a voice conversion playing module;
the receiving module, the voice recognition module, the natural language processing module, the text extraction module and the voice conversion playing module are sequentially connected;
the receiving module is used for receiving voice information of a user;
the voice recognition module is used for carrying out automatic voice recognition according to the received voice information to obtain corresponding character information;
the natural language processing module is used for carrying out natural language processing on the character information and converting the character information into a structured language;
the text extraction module is used for extracting answer text information from a preset database by the intelligent auxiliary robot according to the structured language;
and the voice conversion playing module is used for converting the answer text information into voice and playing the voice from the sound equipment of the intelligent auxiliary robot.
6. An electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors to perform the intelligent assisted robot interaction method of any of claims 1 to 4.
7. A computer-readable storage medium, having stored thereon a computer program which can be loaded and executed by a processor to perform the intelligent assisted robot interaction method of any of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110425094.7A CN113160828A (en) | 2021-04-20 | 2021-04-20 | Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110425094.7A CN113160828A (en) | 2021-04-20 | 2021-04-20 | Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113160828A true CN113160828A (en) | 2021-07-23 |
Family
ID=76867538
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110425094.7A Pending CN113160828A (en) | 2021-04-20 | 2021-04-20 | Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113160828A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114984509A (en) * | 2022-07-22 | 2022-09-02 | 杭州亚辰电子科技有限公司 | Digital resistor fitness system and system data processing method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106952646A (en) * | 2017-02-27 | 2017-07-14 | 深圳市朗空亿科科技有限公司 | A kind of robot interactive method and system based on natural language |
| US9865254B1 (en) * | 2016-02-29 | 2018-01-09 | Amazon Technologies, Inc. | Compressed finite state transducers for automatic speech recognition |
| CN108962281A (en) * | 2018-08-15 | 2018-12-07 | 三星电子（中国）研发中心 | A kind of evaluation of language expression and householder method and device |
| CN111400469A (en) * | 2020-03-12 | 2020-07-10 | 法雨科技(北京)有限责任公司 | Intelligent generation system and method for voice question answering |
| CN112669841A (en) * | 2020-12-18 | 2021-04-16 | 平安科技（深圳）有限公司 | Training method and device for multilingual speech generation model and computer equipment |
-
2021
- 2021-04-20 CN CN202110425094.7A patent/CN113160828A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9865254B1 (en) * | 2016-02-29 | 2018-01-09 | Amazon Technologies, Inc. | Compressed finite state transducers for automatic speech recognition |
| CN106952646A (en) * | 2017-02-27 | 2017-07-14 | 深圳市朗空亿科科技有限公司 | A kind of robot interactive method and system based on natural language |
| CN108962281A (en) * | 2018-08-15 | 2018-12-07 | 三星电子（中国）研发中心 | A kind of evaluation of language expression and householder method and device |
| CN111400469A (en) * | 2020-03-12 | 2020-07-10 | 法雨科技(北京)有限责任公司 | Intelligent generation system and method for voice question answering |
| CN112669841A (en) * | 2020-12-18 | 2021-04-16 | 平安科技（深圳）有限公司 | Training method and device for multilingual speech generation model and computer equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114984509A (en) * | 2022-07-22 | 2022-09-02 | 杭州亚辰电子科技有限公司 | Digital resistor fitness system and system data processing method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| TW546631B (en) | Disambiguation language model | |
| JP5066483B2 (en) | Language understanding device | |
| US10176809B1 (en) | Customized compression and decompression of audio data | |
| JP2011033680A (en) | Voice processing device and method, and program | |
| CN111862954A (en) | Method and device for acquiring voice recognition model | |
| KR101664815B1 (en) | Method for creating a speech model | |
| KR101424193B1 (en) | System And Method of Pronunciation Variation Modeling Based on Indirect data-driven method for Foreign Speech Recognition | |
| JP2004170765A (en) | Apparatus and method for speech processing, recording medium, and program | |
| Boite et al. | A new approach towards keyword spotting. | |
| JP3535292B2 (en) | Speech recognition system | |
| CN113160828A (en) | Intelligent auxiliary robot interaction method and system, electronic equipment and storage medium | |
| CN114974218A (en) | Voice conversion model training method and device and voice conversion method and device | |
| US6963832B2 (en) | Meaning token dictionary for automatic speech recognition | |
| JP4581549B2 (en) | Audio processing apparatus and method, recording medium, and program | |
| Mohanty et al. | Speaker identification using SVM during Oriya speech recognition | |
| CN112084775B (en) | Text error correction method after voice conversion | |
| JPH09134192A (en) | Statistical language model forming device and speech recognition device | |
| KR100736496B1 (en) | performance improvement method of continuation voice recognition system | |
| JP2003271180A (en) | Voice processor, voice processing method, program and recording medium | |
| Vanajakshi et al. | Investigation on large vocabulary continuous Kannada speech recognition | |
| JPH1185184A (en) | Speech recognition device | |
| Khalifa et al. | Statistical modeling for speech recognition | |
| CN112185346B (en) | Multilingual voice keyword detection and model generation method and electronic equipment | |
| JP2975540B2 (en) | Free speech recognition device | |
| Suontausta et al. | Low memory decision tree method for text-to-phoneme mapping |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210723 |