Patent Publication Number: US-2022230633-A1

Title: Speech recognition method and apparatus

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     The present application is based upon and claims priority to Chinese Patent Application No. 202110391076.1, filed on Apr. 12, 2021, the entirety contents of which are incorporated herein by reference. 
     TECHNICAL FIELD 
     The present disclosure relates to the field of computer technology, specially the field of artificial intelligence technologies such as speech recognition and natural language processing, and in particular to a speech recognition method, a speech recognition apparatus, an electronic device and a storage medium. 
     BACKGROUND 
     Currently, voice interaction is a commonly used interaction method in human-computer interaction. For example, in a vehicle, natural language understanding technology can be used to recognize the user&#39;s voice command, and then realize operations such as tilting the sunroof and turning on the air conditioner of the vehicle, so as to provide more convenient, accurate and humanized driving services, to improve the driving experience. 
     For voice interaction, offline voice recognition is an indispensable function. Offline voice recognition not only requires products to be able to convert voice into text through local recognition, but also requires the ability to correctly understand the user&#39;s intention to give corresponding feedback. Therefore, it is particularly important to improve the accuracy of offline speech recognition results. 
     SUMMARY 
     The present disclosure provides a speech recognition method, a speech recognition apparatus, and a storage medium. 
     Embodiments of the present disclosure provide a speech recognition method. The method includes: obtaining an initial recognition result by performing a speech recognition on a sentence to be recognized; obtaining at least one candidate character pinyin string corresponding to each character in the initial recognition result; determining at least one sentence pinyin string corresponding to the initial recognition result based on the at least one candidate character pinyin string corresponding to the character; and generating a pinyin-corrected recognition result by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     Embodiments of the present disclosure provide a speech recognition apparatus. The apparatus includes: a processor, a memory storing instructions executable by the processor, wherein the processor is configured to obtain an initial recognition result by performing a speech recognition on a sentence to be recognized; obtain at least one candidate character pinyin string corresponding to each character in the initial recognition result; determine at least one sentence pinyin string corresponding to the initial recognition result based on the at least one candidate character pinyin string corresponding to the character; and generate a pinyin-corrected recognition result by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     Embodiments of the present disclosure provide a non-transitory computer-readable storage medium storing computer instructions. The computer instructions are configured to cause the computer to implement a speech recognition method. The method includes: obtaining an initial recognition result by performing a speech recognition on a sentence to be recognized; obtaining at least one candidate character pinyin string corresponding to each character in the initial recognition result; determining at least one sentence pinyin string corresponding to the initial recognition result based on the at least one candidate character pinyin string corresponding to the character; and generating a pinyin-corrected recognition result by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Additional features of the present disclosure will be easily understood through the following description. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings are used to better understand the solution and do not constitute a limitation of the present disclosure, in which: 
         FIG. 1  is a flowchart of a speech recognition method according to Embodiment 1 of the present disclosure. 
         FIG. 2  is a flowchart of a speech recognition method according to Embodiment 2 of the present disclosure. 
         FIG. 3  is a flowchart of a speech recognition method according to Embodiment 3 of the present disclosure. 
         FIG. 4  is a flowchart of a speech recognition method according to Embodiment 4 of the present disclosure. 
         FIG. 5  is a schematic diagram of a speech recognition apparatus according to Embodiment 5 of the present disclosure. 
         FIG. 6  is a schematic diagram of a speech recognition apparatus according to Embodiment 6 of the present disclosure. 
         FIG. 7  is a block diagram of an electronic device used to implement the speech recognition method according to an embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     The exemplary embodiments of the present disclosure are described below in combination with the accompanying drawings, which include various details of the embodiments of the present disclosure to aid in understanding, and should be considered merely exemplary. Therefore, those skilled in the art should know that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. For the sake of clarity and brevity, descriptions of well-known features and structures have been omitted from the following description. 
     It is understandable that offline speech recognition is an essential function for voice interaction. Offline speech recognition not only requires the product to be able to convert speech into text through local recognition, but also requires the ability to correctly understand the user&#39;s intention to make corresponding response. Therefore, it is particularly important to improve the accuracy of offline speech recognition results. 
     In order to improve the accuracy of the speech recognition result, the present disclosure provides a speech recognition method. According to the speech recognition method, firstly the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. Further, the pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. Therefore, the accuracy of the speech recognition result is improved. 
     The speech recognition method, the speech recognition apparatus, an electronic device, a non-transitory computer-readable storage medium and a computer program product of the embodiments of the present disclosure are described below with reference to the accompanying drawings. 
     Firstly, the speech recognition method according to the present disclosure will be described in detail with reference to  FIG. 1 . 
       FIG. 1  is a flowchart of a speech recognition method according to Embodiment 1 of the present disclosure. It should be noted that in the speech recognition method of the embodiments, the execution subject is a speech recognition apparatus. The speech recognition apparatus can be an electronic device, and can also be configured in the electronic device, to improve the accuracy of the speech recognition result. The embodiments of the present disclosure are described by taking the speech recognition apparatus configured in the electronic device as an example. 
     The electronic device may be any stationary or mobile computing device capable of data processing, such as mobile computing device such as notebook computers, smart phones, and wearable devices, or stationary computing device such as desktop computers, or servers, or other types of computing devices, which are not limited in this disclosure. 
     As shown in  FIG. 1 , the speech recognition method includes the following steps. 
     In step  101 , an initial recognition result is obtained by performing a speech recognition on a sentence to be recognized. 
     The initial recognition result is obtained by performing off-line speech recognition on the sentence to be recognized using the speech recognition apparatus, or obtained by performing online speech recognition on the sentence to be recognized using the speech recognition apparatus, which is not limited in the present disclosure. 
     Correspondingly, the speech recognition method of the present disclosure can be applied to improve the accuracy of the offline speech recognition result, and can also be applied to improve the accuracy of the online speech recognition result. The application scenarios of the speech recognition method are not limited in the present disclosure. 
     In step  102 , at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. 
     A character pinyin string consists of each letter in the corresponding pinyin of a character. For example, a pinyin string corresponding to “ (Chinese character)” is “shi”, and a pinyin string corresponding to “ (Chinese character)” is “da”. 
     In an exemplary embodiment, the speech recognition apparatus can carry out pinyin conversion character-by- character on the initial recognition result, to convert each character into pinyin in the initial recognition result. It should be noted that in the process of carrying out the pinyin conversion, for each character in the initial recognition result, it is necessary to consider the situation that the character is a polyphonic character and the pronunciation defects such as ambiguous pronunciation of “l” and “r”, ambiguous pronunciation of “h” and “f”, and ambiguous pronunciation of front and rear nasal sounds, which may lead to the situation in which one character corresponds to multiple pinyin strings, thereby obtaining at least one candidate character pinyin string corresponding to each character in the initial recognition result. 
     For example, it is assumed that in a vehicle, the initial recognition result of the sentence to be recognized obtained by the speech recognition apparatus is “ ” (a Chinese sentence). The speech recognition apparatus can perform the pinyin conversion for each character in the initial recognition result, since the Chinese characters of   and “ ” are not polyphonic characters and generally do not have the situation of pronunciation errors, so that a candidate character pinyin string “da” corresponding to “ ”, a candidate character pinyin string “kai” corresponding to “ ” and a candidate character pinyin string “lu” corresponding to “ ” and a candidate character pinyin string “kuang” corresponding to “ ” are obtained. As for the two characters of “ ”, since there may be cases where the pronunciation of “sh” and “s” are ambiguous, thereby, two candidate character pinyin strings “sh” and “s” corresponding to each character of “ ” can be obtained. 
     Alternatively, it is assumed that the initial recognition result of the sentence to be recognized obtained by the speech recognition apparatus is   (Chinese sentence, which means turning on the music”. The speech recognition apparatus can perform the pinyin conversion on each character in the initial recognition result. Since the Chinese characters   and “ ” are not polyphonic characters and usually do not have pronunciation errors, thus a candidate character pinyin string “da” corresponding to “ ”, a candidate character pinyin string “kai” corresponding to “ ”, a candidate character pinyin string “yin” corresponding to “ ”. Since the character of “ ” is a polyphonic character, including the pronunciations “le” and “yue”, two candidate character pinyin strings “le” and “yue” corresponding to “ ” can be obtained. 
     In step  103 , at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. 
     The sentence pinyin string is a pinyin string corresponding to the whole sentence of the initial recognition result. For example,  (a Chinese sentence, which means adjusting the seat)” corresponds to a sentence pinyin string “tiaozhengzuoyi”. 
     In an exemplary embodiment, after the at least one candidate character pinyin string corresponding to each character in the initial recognition result is determined, at least one sentence pinyin string corresponding to the initial recognition result is obtained based on the at least one candidate character pinyin string corresponding to the character. When each character in the initial recognition result corresponds to a pinyin string of a candidate character, a sentence pinyin string corresponding to the initial recognition result is determined. When there is at least one character in the initial recognition result corresponding to multiple sentence pinyin strings, multiple sentence pinyin strings corresponding to the initial recognition result can be determined. 
     For example, based on the above-mentioned example, at least one candidate character pinyin string corresponding to each character in the initial recognition result of   is obtained, four sentence pinyin strings, i.e., “dakaisisilukuang”, “dakaishishilukuang”, “dakaishisilukuang” and “dakaisishilukuang” corresponding to the initial recognition result     are obtained, based on the candidate character pinyin string “da” corresponding to “ ”, the candidate character pinyin string “kai” corresponding to “ ”, two candidate character pinyin strings of “shi” and “si” corresponding to each “ ” respectively, a candidate character pinyin string “lu” corresponding to “ ” and a candidate character pinyin string “kuang” corresponding to “ ”. Similarly, two pinyin strings “dakaiyinyue” and “dakaiyinle” corresponding to the initial recognition result “ ” can be obtained. 
     In step  104 , a pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     In an exemplary embodiment, a pinyin correction database can be set in advance, which includes a plurality of pinyin strings and recognition result corresponding to each pinyin string, so that after the at least one sentence pinyin string corresponding to the initial recognition result is determined, the at least one sentence pinyin string can be matched with each pinyin string in the preset pinyin correction database, so that the identification result corresponding to the pinyin string matched with the at least one sentence pinyin string corresponding to the initial recognition result in the pinyin correction database is determined as the pinyin-corrected identification result, to realize the pinyin correction of the initial identification result. 
     For example, it is assumed that a plurality of pinyin strings and the corresponding identification result of each pinyin string are included in the preset pinyin correction database, such as the pinyin string of “dakaishishilukuang” and the identification result “  (Chinese sentence, which means turning on the real-time traffic monitor)” corresponding to the pinyin string of “dakaishishilukuang”, and the four sentence pinyin strings corresponding to the obtained initial recognition result of “ ”, i.e., “dakaisisilukuang”, “dakaishisilukuang”, “dakaisishilukuang” and “dakaishishilukuang”, then four sentence pinyin strings corresponding to the initial recognition result can be matched with a plurality of pinyin strings in the preset pinyin correction database respectively. Since “dakaishishilukuang” corresponding to the initial recognition result matches “dakaishishilukuang” in the pinyin correction database, the recognition result of “ ” corresponding to “dakaishishilukuang” can be determined as the pinyin-corrected recognition result, so that the initial recognition result of “ ” is corrected to “ ”. 
     According to the speech recognition method, after obtaining the initial recognition result of the sentence to be recognized, pinyin correction is performed on the initial recognition result, and when taking account of polyphonic characters and pronunciation defects when performing the pinyin correction, the at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined. To perform the pinyin correction on the initial recognition result based on the at least one sentence pinyin string, accurate speech recognition is performed on the statement to be recognized that has ambiguous pronunciation due to reasons such as polyphonic characters and pronunciation defects, to improve the accuracy of the speech recognition result. 
     According to the speech recognition method according to the embodiments of the present disclosure, at first, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. The pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. Therefore, the accuracy of the speech recognition result is improved. 
     Based on the above-mentioned analysis, in the embodiments of the present disclosure, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The pinyin-corrected recognition result is generated by performing the pinyin correction on the initial recognition result. In combination with  FIG. 2 , in the speech recognition method according to the present disclosure, the process of performing the pinyin correction on the initial recognition result is further described. 
       FIG. 2  is a flowchart of a speech recognition method according to Embodiment 2 of the present disclosure. 
     As shown in  FIG. 2 , the speech recognition method includes the following steps. 
     In step  201 , an initial recognition result is obtained by performing a speech recognition on a sentence to be recognized. 
     In step  202 , at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. 
     For the specific implementation process and principle of the above steps  201 - 202 , reference may be made to the description of the above embodiments, and details are not repeated here. 
     In step  203 , at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. 
     In an exemplary embodiment, step  203  can be implemented by: for each character, selecting a candidate character pinyin string from the at least one candidate character pinyin string corresponding to the character as a target character pinyin string; splicing target character pinyin strings of selected characters based on a sequence of characters in the initial recognition result; and determining a spliced pinyin string as the sentence pinyin string corresponding to the initial recognition result. 
     For example, suppose that the initial recognition result is “ ”, the candidate character pinyin string “da” corresponding to “ ”, the candidate character pinyin string “kai” corresponding to “ ”, two candidate character pinyin strings of “shi” and “si” corresponding to each “ ” respectively, the candidate character pinyin string “lu” corresponding to “ ” and the candidate character pinyin string “kuang” corresponding to “ ” are obtained. For each character, a candidate character pinyin string is determined from the at least one candidate character pinyin string corresponding to the character as the target character pinyin string. Assuming that “da”, “kai”, “shi” and “si”, “lu” and “kuang” are selected as the target character pinyin strings, according to the order of   and “ ”, the selected multiple target character pinyin strings are spliced to obtain the sentence pinyin string of “dakaisisilukuang” corresponding to the initial recognition result. 
     Similarly, when “da”, “kai”, “shi” and “si”, “lu” and “kuang” are selected as the target character pinyin strings, these target character pinyin strings are spliced according to the order of   and “ ”, to obtain the sentence pinyin string of “dakaishisilukuang” corresponding to the initial recognition result. When “da”, “kai”, “si” and “shi”, “lu” and “kuang” are selected as the target character pinyin strings, these target character pinyin strings are spliced according to the order of   and “ ”, to obtain the sentence pinyin string of “dakaisishilukuang” corresponding to the initial recognition result. When “da”, “kai”, “shi” and “shi”, “lu” and “kuang” are selected as the target character pinyin strings, these target character pinyin strings are spliced according to the order of   and “ ”, to obtain the sentence pinyin string of “dakaishishilukuang” corresponding to the initial recognition result. 
     Based on the above-mentioned example, in the embodiments of the present disclosure, in each character corresponding to initial recognition result, when each character corresponds to a character pinyin string, the initial recognition result corresponds to a sentence pinyin string. In each character corresponding to the initial recognition result, when at least one character corresponds to multiple character pinyin strings, the initial recognition result corresponds to multiple sentence pinyin strings, and the number of sentence pinyin strings is a product of a number of character pinyin strings corresponding to each character in the initial recognition result. 
     Taking the initial recognition result corresponding to a plurality of sentence pinyin strings as an example, the process of carrying out the pinyin correction on the initial recognition result according to the plurality of sentence pinyin strings is described. 
     In step  204 , each of the plurality of sentence pinyin strings is matched with a plurality of pinyin strings to be corrected in a pinyin correction database, in which the pinyin correction database includes the plurality of pinyin strings to be corrected, a corrected pinyin string corresponding to each pinyin string to be corrected, and a recognition result corresponding to the corrected pinyin string. 
     In step  205 , in response to that there is a pinyin string to be corrected that matches the sentence pinyin string in the pinyin correction database, the corrected pinyin string corresponding to the pinyin string to be corrected that matches the sentence pinyin string is determined as a target corrected pinyin string. 
     In step  206 , a recognition result corresponding to the target corrected pinyin string is determined as the pinyin-corrected recognition result. 
     In an exemplary embodiment, the pinyin correction database can be preset. The pinyin correction database includes a plurality of pinyin strings to be corrected, the corrected pinyin string corresponding to each pinyin string to be corrected and the recognition result corresponding to the corrected pinyin string. Thus, after determining the plurality of sentence pinyin strings corresponding to the initial recognition result, for each sentence pinyin string in the plurality of sentence pinyin strings, the sentence pinyin string is matched with a plurality of pinyin strings to be corrected in the pinyin correction database. In response to that there is a pinyin string to be corrected that matches the sentence pinyin string in the pinyin correction database, the corrected pinyin string corresponding to the pinyin string to be corrected that matches the sentence pinyin string is determined as a target corrected pinyin string. Then, a recognition result corresponding to the target corrected pinyin string is determined as the pinyin-corrected recognition result, to realize the pinyin correction of the initial recognition result. 
     For example, suppose that as shown in Table 1, the preset pinyin correction database includes a plurality of pinyin strings to be corrected, a corrected pinyin string corresponding to each pinyin string to be corrected, and a recognition result corresponding to the corrected pinyin string. 
     
       
         
           
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Part of the data stored in the pinyin correction database 
               
               
                   
               
             
            
               
                   
               
            
           
           
               
               
               
            
               
                 pinyin string to be  
                 corrected pinyin  
                 recognition result  
               
               
                 corrected 
                 string 
                 corresponding to the  
               
               
                   
                   
                 corrected pinyin string 
               
               
                 zangsan, zhangsan, 
                 zhangsan 
                     (a Chinese name) 
               
               
                 zangshan, zangsan 
                   
                   
               
               
                 lisi, lishi 
                 lisi 
                     (a Chinese name) 
               
               
                 dakaisisilukuang, 
                 dakaishishilukuang 
                     (a Chinese  
               
               
                 dakaishishilukuang, 
                   
                 sentence, which means  
               
               
                 dakaishisilukuang, 
                   
                 turning on the real-time  
               
               
                 dakaisishilukuang 
                   
                 traffic monitor) 
               
               
                 dakaihoubeixiang, 
                 dakaihoubeixiang 
                     (a Chinese  
               
               
                 dakaihoubeixian, 
                   
                 sentence, which means 
               
               
                   
                   
                 opening the trunk) 
               
               
                 qiaoqitianchuang, 
                 qiaoqitianchuang 
                     (a Chinese  
               
               
                 qiaoqitianchuan 
                   
                 sentence, which means  
               
               
                   
                   
                 tilting the sunroof) 
               
               
                   
               
            
           
         
       
     
     Assuming that the sentence pinyin strings corresponding to the initial recognition result of “ ” are “dakaisisilukuang”, “dakaishisilukuang”, “dakaisishilukuang” and “dakaishishilukuang”, then each sentence pinyin string of the four sentence pinyin strings corresponding to the initial recognition result is matched with a plurality of pinyin strings to be corrected in the preset pinyin correction database. For the above-mentioned 4 sentence pinyin strings, there are matching pinyin strings to be corrected in preset pinyin correction database, the corrected pinyin string corresponding to the pinyin string to be corrected matching the 4 sentence pinyin strings is determined as the target corrected pinyin string. Since the corrected pinyin string corresponding to the pinyin string to be corrected matching the 4 sentence strings is “dakaishishilukuang”, then “dakaishishilukuang” can be determined as the target corrected pinyin string, and the recognition result of “ ” corresponding to “dakaishishilukuang” can be determined as the pinyin-corrected recognition result. 
     It should be noted that, when there are a plurality of sentence pinyin strings corresponding to the initial recognition result, for each sentence pinyin string in the plurality of sentence pinyin strings, after the sentence pinyin string is matched with a plurality of pinyin strings to be corrected in the pinyin correction database, if there are pinyin strings to be corrected that match the plurality of sentence pinyin strings respectively, and the plurality of pinyin strings to be corrected correspond to different corrected pinyin strings, it is necessary to determine the recognition results corresponding to the plurality of different corrected pinyin strings respectively as the pinyin-corrected identification results. 
     According to the speech recognition method of the embodiments of the present disclosure, after obtaining at least one candidate character pinyin string corresponding to each character in the initial recognition result, for each character, a candidate character pinyin string is selected from the at least one candidate character pinyin string corresponding to the character as a target character pinyin string. Then, target character pinyin strings of selected characters are spliced based on a sequence of characters in the initial recognition result. Thus the pinyin string after the splicing is determined as the sentence pinyin string corresponding to the initial recognition result, in response to that at least one character of the initial recognition result corresponds to a plurality of character pinyin strings, a plurality of sentence pinyin strings corresponding to the initial recognition result are obtained, and then each sentence pinyin string in the plurality of sentence pinyin strings is matched with the plurality of pinyin strings to be corrected in the pinyin correction database. The pinyin-corrected identification result can be obtained according to the matching result, compared to directly matching the initial recognition result with the recognition result to be corrected and the corrected recognition result in the database through Chinese matching mode, to carry out the mode of correcting the initial recognition result, the matching success rate of the sentence pinyin string with the pinyin string to be corrected in the pinyin correction database is higher, thereby improving the correction rate of the initial recognition result, and then improving the accuracy rate of the speech recognition result. 
     Known by above-mentioned analysis, in the embodiments of the present disclosure, the speech recognition is performed on the sentence to be recognized, to obtain the initial recognition result. The pinyin correction is performed on the initial recognition result, to generate the pinyin-corrected recognition result. In exemplary implementation, there may be situations where the pinyin correction is unsuccessfully performed in the pinyin-corrected identification result, for example, there is no pinyin string to be corrected that matches the sentence pinyin string corresponding to the initial identification result in the pinyin correction database, or there may be errors in proper nouns in the pinyin-corrected identification result. For example, when the “   (trunk)” is identified as the “ ”. For the above situation, in combination with  FIG. 3 , the speech recognition method of the present disclosure will be further described. 
       FIG. 3  is a flowchart of a speech recognition method according to Embodiment 3 of the present disclosure. As shown in  FIG. 3 , the speech recognition method includes the following steps. 
     In step  301 , an initial recognition result is obtained by performing a speech recognition on a sentence to be recognized. 
     In step  302 , at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. 
     In step  303 , at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. 
     In step  304 , a pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     For the specific implementation process and principle of steps  301 - 304 , reference may be made to the description of the above-mentioned embodiments, which will not be repeated here. 
     In step  305 , each of the plurality of sentence pinyin strings is matched with a plurality of pinyin strings to be corrected in a pinyin correction database, in which the pinyin correction database includes the plurality of pinyin strings to be corrected, a corrected pinyin string corresponding to each pinyin string to be corrected, and a recognition result corresponding to the corrected pinyin string. 
     Proper nouns are nouns unique to people, places and things, such as “ (a Chinese noun, which means a trunk)” and “ (a Chinese noun, which means a seat)”. 
     In step  306 , in response to that there is a pinyin string to be corrected that matches the sentence pinyin string in the pinyin correction database, the corrected pinyin string corresponding to the pinyin string to be corrected that matches the sentence pinyin string is determined as a target corrected pinyin string. 
     In step  307 , a recognition result corresponding to the target corrected pinyin string is determined as the pinyin-corrected recognition result. 
     In an exemplary embodiment, a proper noun database can be preset. The proper noun database includes a plurality of recognition results to be corrected, and a corrected recognition result corresponding to each of the plurality of recognition results to be corrected. After generating the pinyin-corrected recognition result, the pinyin-corrected recognition result is matched with a plurality of recognition results to be corrected in a proper noun database, in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin-corrected recognition result is determined as a target recognition result to be corrected. A corrected recognition result corresponding to the target recognition result to be corrected is determined as a proper-noun-corrected recognition result. 
     It should be noted that, in the embodiments of the present disclosure, the mode that each sentence pinyin string corresponding to the initial recognition result is matched with the pinyin string to be corrected in the preset pinyin correction database in the above-described embodiments is adopted to perform the pinyin correction on the initial recognition result, to obtain the pinyin-corrected recognition result. In a possible implementation, for one or more sentence pinyin strings corresponding to the initial recognition result, there may be matching pinyin strings to be corrected in the pinyin correction database, at this moment, the corresponding pinyin string to be corrected corresponding to the matching pinyin string is determined to be the target corrected pinyin string, the identification result corresponding to the target corrected pinyin string is determined as the pinyin-corrected identification result, and the pinyin-corrected identification result is matched with the plurality of identification results to be corrected in the proper noun database. In another possible implementation, there may not be a pinyin string to be corrected that matches any sentence pinyin string corresponding to the initial recognition result in the pinyin correction database, that is, the target corrected pinyin string is not obtained. At this time, the initial recognition result is determined as the pinyin-corrected recognition result, which is matched with the plurality of recognition results to be corrected in the proper noun database. 
     That is, in the embodiments of the present disclosure, after successfully obtaining the pinyin-corrected recognition result of the initial recognition result through the pinyin correction, further proper noun correction is performed on the pinyin-corrected recognition result, and when the pinyin-corrected recognition result of the initial identification result is not obtained successfully through the pinyin correction, the proper noun correction is directly performed on the initial recognition result. 
     For example, it is assumed that the preset proper noun database includes a plurality of recognition results to be corrected, and a corrected recognition result corresponding to each of the plurality of recognition results to be corrected, including the identification result to be corrected “ (a wrong Chinese sentence, which means opening the backup line)” and the corresponding recognition result of “ (a Chinese sentence, which means opening the trunk)”. Suppose the initial recognition result is “ ”, and when the pinyin correction is performed, there is no pinyin string to be corrected that matches any one sentence pinyin string in the at least one sentence pinyin string corresponding to “ ” in the pinyin correction database, that is, the pinyin-corrected recognition result of the initial recognition result is unsuccessfully obtained through the pinyin correction, then the initial recognition result of “   ” is determined as the pinyin-corrected recognition result, which can be matched with the plurality of the recognition results to be corrected in the proper noun database. Since there is a recognition result to be corrected that matches “ ” in the proper noun database, the recognition result to be corrected that matches “ ” can be determined as the target recognition result to be corrected, and the corrected identification result of “ ” corresponding to the identification result to be corrected is determined as the proper-noun-corrected recognition result. 
     According to the speech recognition method according to the embodiments of the present disclosure, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. The pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. The pinyin-corrected recognition result is matched with a plurality of identification results to be corrected in the proper noun database, in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin-corrected recognition result is determined as a target recognition result to be corrected. A corrected recognition result corresponding to the target recognition result to be corrected is determined as a proper-noun-corrected recognition result. Therefore, the accuracy of the speech recognition result is further improved. 
     Based on the above-mentioned analysis, in the embodiments of the present disclosure, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The pinyin-corrected recognition result is generated by performing the pinyin correction on the initial recognition result, the proper nouns correction is performed on the pinyin-corrected recognition result, to further improve the accuracy of the speech recognition result. In the exemplary embodiment, the proper-noun-corrected recognition result may have a whole sentence error, for example, the result does not match the actual speech recognition application scenario, and the sentence “ (a Chinese sentence, which means that I am bored)” required to instruct the sunroof of the vehicle to open is identified as “ (a Chinese sentence, which means that I am busy)”. In view of the above situation, the speech recognition method according to the present disclosure will be further described below with reference to  FIG. 4 . 
       FIG. 4  is a flowchart of a speech recognition method according to Embodiment 4 of the present disclosure. As shown in  FIG. 4 , the speech recognition method includes the following steps. 
     In step  401 , an initial recognition result is obtained by performing a speech recognition on a sentence to be recognized. 
     In step  402 , at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. 
     In step  403 , at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. 
     In step  404 , a pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     In step  405 , the pinyin-corrected recognition result is matched with a plurality of recognition results to be corrected in a proper noun database, the proper noun database includes a plurality of recognition results to be corrected, and a corrected recognition result corresponding to each of the plurality of recognition results to be corrected. 
     In step  406 , in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin-corrected recognition result is determined as a target recognition result to be corrected. 
     In step  407 , a corrected recognition result corresponding to the target recognition result to be corrected is determined as a proper-noun-corrected recognition result. 
     For the specific implementation process and principle of the above steps  401  - 407 , reference may be made to the description of the above embodiments, and details are not repeated here. 
     In step  408 , the proper-noun-corrected recognition result is matched with a plurality of whole sentence recognition results to be corrected in a whole sentence correction database, the whole sentence correction database includes a plurality of whole sentence recognition results to be corrected, and a corrected whole sentence recognition result corresponding to each of the plurality of whole sentence recognition results to be corrected. 
     In step  409 , in response to that there is a whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result in the whole sentence correction database, the whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result is determined as a target whole sentence recognition result to be corrected. 
     In step  410 , a corrected whole sentence recognition result corresponding to the target whole sentence recognition result to be corrected is determined as a whole-sentence-corrected recognition result. 
     In an exemplary embodiment, the whole sentence correction database can be preset. The whole sentence correction database includes a plurality of whole sentence recognition results to be corrected, and a corrected whole sentence recognition result corresponding to each of the plurality of whole sentence recognition results to be corrected. Therefore, after determining the proper-noun-corrected recognition result, the proper-noun-corrected recognition result is matched with a plurality of whole sentence recognition results to be corrected in the whole sentence correction database, in response to that there is a whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result in the whole sentence correction database, the whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result is determined as a target whole sentence recognition result to be corrected. A corrected whole sentence recognition result corresponding to the target whole sentence recognition result to be corrected is determined as a whole-sentence-corrected recognition result. 
     A plurality of whole sentence recognition results to be corrected in the whole sentence correction database, and the whole-sentence-corrected recognition result corresponding to each whole sentence recognition result to be corrected, can be set with reference to each interaction sentence in the speech recognition application scenario and the corresponding common error recognition results. For example, in a vehicle, the operation of opening the window is instructed by “ (a Chinese sentence, which means that I am bored)”, which could be misidentified as “ (a Chinese sentence, which means that I am silly)” and “ (a Chinese sentence, which means that I am busy)”, then the whole sentence correction database may include the recognition results of the whole sentence to be corrected “ ” and “ ”, and the corresponding whole-sentence-corrected recognition result of “ ”. 
     It should be noted that, in the embodiments of the present disclosure, in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin -corrected recognition result is determined as a target recognition result to be corrected, a corrected recognition result corresponding to the target recognition result to be corrected is determined as a proper-noun-corrected recognition result. When there is no identification result to be corrected that matches the pinyin-corrected identification result in the proper noun database, the pinyin-corrected identification result is determined as the proper-noun-corrected recognition result, which is matched with the plurality of whole sentence recognition results to be corrected in the whole sentence correction database. 
     That is, in the embodiments of the present disclosure, after the proper-noun-corrected recognition result is obtained successfully by proper noun correction, whole sentence correction is performed on the proper-noun-corrected recognition result. Alternatively, when the proper-noun-corrected recognition result is not obtained successfully through proper noun correction, it is also possible to perform the whole sentence correction directly on the pinyin-corrected identification result. The pinyin-corrected identification result here may be the pinyin-corrected identification result obtained successfully through the pinyin correction, or the initial identification result when the pinyin correction has not been successfully performed, which is not limited in the present disclosure. 
     For example, it is assumed that the preset whole sentence correction database includes a plurality of whole sentence recognition results to be corrected, and the corrected whole sentence recognition result corresponding to each whole sentence recognition result to be corrected, including the whole-sentence-corrected recognition results of “ ” and “ ”, and the corresponding whole-sentence-corrected recognition result of “ ”. Assuming that proper-noun-corrected recognition result is “ ”, the recognition result is matched with a plurality of whole sentences to be corrected in the whole sentence correction database. Since there are whole sentence recognition results to be corrected matching “ ” in the whole sentence correction database, the whole sentence recognition results to be corrected matching “ ” is determined as the target whole sentence recognition results to be corrected, and the corrected whole sentence recognition result “ ” corresponding to “ ” is determined as the whole-sentence-corrected recognition result, so as to perform the operation of opening the sunroof of the vehicle. 
     According to the speech recognition method according to the embodiments of the present disclosure, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. The pinyin -corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. The pinyin-corrected recognition result is matched with a plurality of identification results to be corrected in the proper noun database, in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin-corrected recognition result is determined as a target recognition result to be corrected. A corrected recognition result corresponding to the target recognition result to be corrected is determined as a proper-noun-corrected recognition result. Therefore, the accuracy of the speech recognition result is further improved. 
     According to the speech recognition method according to the embodiments of the present disclosure, the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. After performing the pinyin correction and the proper nouns correction on the initial recognition result, the proper-noun-corrected recognition result is matched with the plurality of whole sentence recognition results to be corrected in the whole sentence correction database. When there is a whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result in the whole sentence correction database, the whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result is determined as the target whole sentence recognition result to be corrected. The corrected whole sentence recognition result corresponding to the target whole sentence recognition result to be corrected is determined as the corrected whole sentence recognition result. Therefore, the accuracy of speech recognition result is further improved. In addition, in the speech recognition method according to the embodiments of the present disclosure, after the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized, the preset pinyin correction database, the proper noun database and the whole sentence correction database are adopted for database query operation, to perform the pinyin correction, the proper noun correction and the whole sentence correction on the initial recognition result, so that the speech recognition engine does not need to have the function of providing a recognition result set, thus the dependence on the speech recognition engine during speech recognition is reduced, the flexibility of speech recognition is improved, and since the correction process of the initial recognition result is a database query operation, the consumption of performance resources is small. 
     The speech recognition apparatus according to the present disclosure will be described below with reference to  FIG. 5 . 
       FIG. 5  is a schematic diagram of a speech recognition apparatus according to Embodiment 5 of the present disclosure. 
     As shown in  FIG. 5 , the speech recognition apparatus  500  according to the present disclosure includes: a recognizing module  501 , an obtaining module  502 , a first determining module  503  and a generating module  504 . 
     The recognizing module  501  is configured to obtain an initial recognition result by performing a speech recognition on a sentence to be recognized. 
     The obtaining module  502  is configured to obtain at least one candidate character pinyin string corresponding to each character in the initial recognition result. 
     The first determining module  503  is configured to determine at least one sentence pinyin string corresponding to the initial recognition result based on the at least one candidate character pinyin string corresponding to the character. 
     The generating module  504  is configured to generate a pinyin-corrected recognition result by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. 
     It should be noted that, the speech recognition apparatus according to the embodiments can execute the speech recognition method described in the preceding embodiments. The speech recognition apparatus may be an electronic device, or may be configured in the electronic device, so as to improve the accuracy of the speech recognition result. 
     The electronic device may be any stationary or mobile computing device capable of data processing, such as mobile computing device such as notebook computers, smart phones, and wearable devices, or stationary computing device such as desktop computers, or servers, or other types of computing devices, which are not limited in the present disclosure. 
     It should be noted that the foregoing description of the embodiments of the speech recognition method is also applicable to the speech recognition apparatus according to the present disclosure, and details are not repeated here. 
     With the speech recognition apparatus according to the embodiment of the present disclosure, firstly the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. Further, the pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. Therefore, the accuracy of the speech recognition result is improved. 
     The speech recognition apparatus according to the present disclosure will be described below with reference to  FIG. 6 . 
       FIG. 6  is a schematic diagram of a speech recognition apparatus according to Embodiment 6 of the present disclosure. 
     As shown in  FIG. 6 , the speech recognition apparatus  600  may include: a recognizing module  601 , an obtaining module  602 , a first determining module  603  and a generating module  604 . The recognizing module  601 , the obtaining module  602 , the first determining module  603  and the generating module  604  shown in  FIG. 6  have the same function and structure as the recognizing module  501 , the obtaining module  502 , the first determining module  503  and the generating module  504  shown in  FIG. 5 . 
     In an example embodiment, the first determining module  603  includes: a selecting unit, a splicing unit and a first determining unit. 
     The selecting unit is configured to, for each character, select a candidate character pinyin string from the at least one candidate character pinyin string corresponding to the character as a target character pinyin string. 
     The splicing unit is configured to splice target character pinyin strings of selected characters based on a sequence of characters in the initial recognition result. 
     The first determining unit is configured to determine a spliced pinyin string as the sentence pinyin string corresponding to the initial recognition result. 
     In an example embodiment, there are a plurality of sentence pinyin strings, and the generating module includes: a matching unit, a second determining unit and a third determining unit. 
     The matching unit is configured to match each of the plurality of sentence pinyin strings with a plurality of pinyin strings to be corrected in a pinyin correction database, in which the pinyin correction database includes the plurality of pinyin strings to be corrected, a corrected pinyin string corresponding to each pinyin string to be corrected, and a recognition result corresponding to the corrected pinyin string. 
     The second determining unit is configured to determine, in response to that there is a pinyin string to be corrected that matches the sentence pinyin string in the pinyin correction database, the corrected pinyin string corresponding to the pinyin string to be corrected that matches the sentence pinyin string as a target corrected pinyin string. 
     The third determining unit is configured to determine a recognition result corresponding to the target corrected pinyin string as the pinyin-corrected recognition result. 
     In an example embodiment, the apparatus  600  further includes: a first matching module  605 , a second determining module  606  and a third determining module  607 . 
     The first matching module  605  is configured to match the pinyin-corrected recognition result with a plurality of recognition results to be corrected in a proper noun database, in which the proper noun database includes a plurality of recognition results to be corrected, and a corrected recognition result corresponding to each of the plurality of recognition results to be corrected. 
     The second determining module  606  is configured to determine, in response to that there is a recognition result to be corrected that matches the pinyin-corrected recognition result in the proper noun database, the recognition result to be corrected that matches the pinyin-corrected recognition result as a target recognition result to be corrected. 
     The third determining module  607  is configured to determine a corrected recognition result corresponding to the target recognition result to be corrected as a proper-noun-corrected recognition result. 
     In an example embodiment, the apparatus  600  further includes: a second matching module  608 , a fourth determining module  609  and a fifth determining module  610 . 
     The second matching module  608  is configured to match the proper-noun-corrected recognition result with a plurality of whole sentence recognition results to be corrected in a whole sentence correction database, in which the whole sentence correction database includes a plurality of whole sentence recognition results to be corrected, and a corrected whole sentence recognition result corresponding to each of the plurality of whole sentence recognition results to be corrected. 
     The fourth determining module  609  is configured to determine, in response to that there is a whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result in the whole sentence correction database, the whole sentence recognition result to be corrected that matches the proper-noun-corrected recognition result as a target whole sentence recognition result to be corrected. 
     The fifth determining module  610  is configured to determine a corrected whole sentence recognition result corresponding to the target whole sentence recognition result to be corrected as a whole-sentence-corrected recognition result. 
     It should be noted that the foregoing description of the embodiment of the speech recognition method is also applicable to the speech recognition apparatus according to the present disclosure, and will not be repeated here. 
     With the speech recognition apparatus according to the embodiment of the present disclosure, firstly the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. Further, the pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. Therefore, the accuracy of the speech recognition result is improved. 
     According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product. 
       FIG. 7  is a block diagram of an electronic device  700  according to embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relations, and their functions are merely examples, and are not intended to limit the implementation of the present disclosure described and/or required herein. 
     As illustrated in  FIG. 7 , the device  700  includes a computing unit  701  performing various appropriate actions and processes based on computer programs stored in a read-only memory (ROM)  702  or computer programs loaded from the storage unit  708  to a random access memory (RAM)  703 . In the RAM  703 , various programs and data required for the operation of the device  800  are stored. The computing unit  701 , the ROM  702 , and the RAM  703  are connected to each other through a bus  704 . An input/output (I/O) interface  705  is also connected to the bus  704 . 
     Components in the device  700  are connected to the I/O interface  705 , including: an inputting unit  706 , such as a keyboard, a mouse; an outputting unit  707 , such as various types of displays, speakers; a storage unit  708 , such as a disk, an optical disk; and a communication unit  709 , such as network cards, modems, wireless communication transceivers, and the like. The communication unit  709  allows the device  700  to exchange information/data with other devices through a computer network such as the Internet and/or various telecommunication networks. 
     The computing unit  701  may be various general-purpose and/or dedicated processing components with processing and computing capabilities. Some examples of computing unit  701  include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated AI computing chips, various computing units that run machine learning model algorithms, and a digital signal processor (DSP), and any appropriate processor, controller and microcontroller. The computing unit  701  executes the various methods and processes described above, such as the speech recognition method. For example, in some embodiments, the method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit  708 . In some embodiments, part or all of the computer program may be loaded and/or installed on the device  700  via the ROM  702  and/or the communication unit  709 . When the computer program is loaded on the RAM  703  and executed by the computing unit  701 , one or more steps of the method described above may be executed. Alternatively, in other embodiments, the computing unit  701  may be configured to perform the speech recognition method in any other suitable manner (for example, by means of firmware). 
     Various implementations of the systems and techniques described above may be implemented by a digital electronic circuit system, an integrated circuit system, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), System on Chip (SOCs), Load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or a combination thereof. These various embodiments may be implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general programmable processor for receiving data and instructions from the storage system, at least one input device and at least one output device, and transmitting the data and instructions to the storage system, the at least one input device and the at least one output device. 
     The program code configured to implement the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to the processors or controllers of general-purpose computers, dedicated computers, or other programmable data processing devices, so that the program codes, when executed by the processors or controllers, enable the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may be executed entirely on the machine, partly executed on the machine, partly executed on the machine and partly executed on the remote machine as an independent software package, or entirely executed on the remote machine or server. 
     In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), electrically programmable read-only-memory (EPROM), flash memory, fiber optics, compact disc read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. 
     In order to provide interaction with a user, the systems and techniques described herein may be implemented on a computer having a display device (e.g., a Cathode Ray Tube (CRT) or a Liquid Crystal Display (LCD) monitor for displaying information to a user); and a keyboard and pointing device (such as a mouse or trackball) through which the user can provide input to the computer. Other kinds of devices may also be used to provide interaction with the user. For example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or haptic feedback), and the input from the user may be received in any form (including acoustic input, voice input, or tactile input). 
     The systems and technologies described herein can be implemented in a computing system that includes background components (for example, a data server), or a computing system that includes middleware components (for example, an application server), or a computing system that includes front-end components (for example, a user computer with a graphical user interface or a web browser, through which the user can interact with the implementation of the systems and technologies described herein), or include such background components, intermediate computing components, or any combination of front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), the Internet and Block-chain network. 
     The computer system may include a client and a server. The client and server are generally remote from each other and interacting through a communication network. The client-server relation is generated by computer programs running on the respective computers and having a client-server relation with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the problem that there are the defects of difficult management and weak business expansion in the traditional physical hosts and (Virtual Private Server) VPS services. The server may be a server of a distributed system, or a server combined with a block-chain. 
     The present disclosure relates to the field of computer technology, in particular to the field of artificial intelligence technologies such as speech recognition and natural language processing. 
     It is noted that artificial intelligence is a discipline that studies certain thinking processes and intelligent behaviors (such as learning, reasoning, thinking and planning) that allow computers to simulate life, which has both hardware-level technologies and software-level technologies. Artificial intelligence hardware technology generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing. Artificial intelligence software technology generally includes computer vision technology, speech recognition technology, natural language processing technology, and its learning/deep learning, big data processing technology, knowledge map technology and other aspects. 
     According to the technical solution of the embodiments of the present disclosure, firstly the initial recognition result is obtained by performing the speech recognition on the sentence to be recognized. The at least one candidate character pinyin string corresponding to each character in the initial recognition result is obtained. The at least one sentence pinyin string corresponding to the initial recognition result is determined based on the at least one candidate character pinyin string corresponding to the character. Further, the pinyin-corrected recognition result is generated by performing pinyin correction on the initial recognition result based on the at least one sentence pinyin string. Therefore, the accuracy of the speech recognition result is improved. 
     It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present disclosure could be performed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in the present disclosure is achieved, which is not limited herein. 
     The above specific embodiments do not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent replacement and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.