Patent Abstract:
A method of teaching pronunciation is provided which includes communicating by a voice portal server to a user a model word and detecting a response by the user to the voice portal server. The method also includes comparing the response word to the model word and determining a confidence level based on the comparison of the response word to the model word. The method further includes comparing an acceptance limit to the confidence level and confirming a correct pronunciation of the model word if the confidence level one of equals and exceeds the acceptance limit.

Full Description:
FIELD OF THE INVENTION 
   The present invention relates to a method of language instruction, and a system and device for implementing the method. In particular, the present invention relates to a method for learning a language using a voice portal. 
   BACKGROUND INFORMATION 
   Learning a new language may be a difficult task. With increasing globalization, being able to communicate in multiple languages has also become a skill that may provide an edge, including, for example, in career advancement. The quality of the experience of visiting a country, whether for pleasure or business, may be enhanced by even a rudimentary knowledge of the local language. There are various ways to learn a language, including by reading books, taking classes, viewing internet sites, and listening to books-on-tape. 
   It is believed that an important aspect of learning a language is learning correct pronunciation and language usage. Practicing pronunciation and usage may be a critical aspect of properly learning a language. 
   It is believed that available language learning tools may have various disadvantages. For example, learning from a book or books-on-tape is not an interactive process, and therefore the student may fall into the habit of incorrect usage. Attending a class may be helpful, but it may also be inconvenient because of a busy schedule, especially for professionals. Also, students may lose interest in learning if they feel that they are not able to cope with the pace of the class. 
   A tool that teaches pronunciation and usage, and which can be used at the student&#39;s own leisure, would be very convenient and useful. It is therefore believed that there is a need for providing a method and system of providing convenient, effective and/or inexpensive language instruction. 
   SUMMARY OF THE INVENTION 
   An exemplary method of the present invention is directed to providing teaching pronunciation which includes communicating by a voice portal server to a user a model word and detecting a response by the user to the voice portal server. The exemplary method also includes comparing the response word to the model word and determining a confidence level based on the comparison of the response word to the model word, and comparing an acceptance limit to the confidence level and confirming a correct pronunciation of the model word if the confidence level one of equals and exceeds the acceptance limit. 
   An exemplary system of the present invention is directed to providing a system which includes a voice portal, a communication device adapted to be coupled with the voice portal server, and an application server adapted to be electrically coupled with the voice portal. In the exemplary system, the voice portal compares at least one word spoken by a user into the communication device with a phrase provided by the application server to determine a confidence level. 
   An exemplary method of the present invention is directed to providing for a language teaching method which includes communicating a prompt to a user by a voice portal, detecting a response by the user to the voice portal, parsing the response into at least one uttered phrase, each of the at least one uttered phrase associated with a corresponding at least one slot. The exemplary method further includes comparing each of the at least one uttered phrase associated with the corresponding at least one slot with at least one stored phrase, the at least one stored phrase associated with the corresponding at least one slot, and determining a confidence level based on the comparison of each uttered phrase with each stored phrase corresponding to the at least one slot. The exemplary method further includes comparing an acceptance limit to each confidence level, the acceptance limit associated with each stored phrase, and confirming that at least one uttered phrase corresponds to each stored phrase if the confidence level of one equals or exceeds the associated acceptance limit. 
   The exemplary method and/or system of the present invention may provide a user accessible service which may be used at the user&#39;s convenience, at any time. The exemplary system may track a user&#39;s knowledge, experience, and progress. The exemplary system may check on the pronunciation of words/phrases/sentences, as well as identify the correct word usage with an incorrect pronunciation. The exemplary system may also assess a user&#39;s performance (such information may be used to decide to go to the next level), and may make scheduled calls to improve a user&#39;s interaction skills and readiness in the foreign language. The user may be able to decide to be trained on specific topics or grammars (such as, for exemple, financial or technical). 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  shows an exemplary embodiment of a system of the present invention showing a user, a voice portal and a database. 
       FIG. 2  shows an exemplary method according to the present invention, in the form of a flow chart demonstrating a dialogue structure for a user calling the service. 
       FIG. 3  shows an exemplary method according to the present invention, in the form of a flow chart demonstrating a test environment that provides an interactive learning tool for the users to help improve their language skills in the specified language. 
       FIG. 4  shows schematically a virtual classroom including components of the voice portal server, interactive units and the user. 
       FIG. 5  shows an exemplary response parsed into slots and showing various possible uttered phrases. 
   

   DETAILED DESCRIPTION 
   The voice portal may be used as an interactive tool to learn a new language. Speech recognition and playback features may enable the system to provide a simulated, classroom-like environment to the user. According to an exemplary method of the present invention, the method provides an interactive tool that can correct pronunciation and grammar and that can be accessed at any time. 
     FIG. 1  shows a schematic diagram of the system. A voice portal (also referred to as a voice portal server)  12  may be used to recognize proper pronunciation and may be used as an interactive language instruction tool.  FIG. 1  shows the voice portal  12  which operates as an interactive tool for learning a language. A user  10  may call the voice portal  12 . The voice portal  12  may then pull up the profile of the user  10  and begin providing the user  10  with a corresponding tutorial. 
   The user  10  may use a telephone  11  to access the voice portal  12  by calling a telephone number. Alternative methods for the user  10  to access the voice portal  12  may include the use of a personal computer. The voice portal  12  may access a database  13 , which may include a pool of valid, stored phrases (alternatively referred to as grammar files) for various languages, including different dialects within each language. The database  13  may also include different lesson plans depending on the student goals (for example, traveling, conversation, business, academic, etc.). The database  13  may also include a record of the previous lessons presented to user  10 , as well as a progress report which may include areas of strengths and weaknesses. 
   An exemplary system of the present invention may introduce the use of the voice portal  12  as a tool for learning specific languages. The system may provide a structured learning process to the user  10  through a simple call to the voice portal  12 . This instruction may include tutorials and tests to provide the user  10  with a class-like environment, and may provide the user  10  with the flexibility to take lessons and practice by calling the voice portal  12  at any time. 
   The voice portal  12  may include a server connected to the telephone system or another communication network to provide speech recognition and text-to-speech capabilities over the telephone  11  or another communication device. The voice portal  12  may be used to provide different types of information, including, for example, news, weather reports, stock quotes, etc. The voice portal  12  may also maintain profiles of the user  10 , so that the user  10  can access E-mail, a calendar, or address entries. 
   An exemplary system of the present invention uses the voice portal  12  to replicate a language class with pseudo student-teacher interaction. The voice portal  12  operates as a “teacher” to correct the student (the user  10 ), by providing the user  10  with a method of immediate feedback on correctly pronouncing words and correctly using grammar. The voice portal  12  can also store a profile of the user  10 . By keeping track of the sessions of the user  10 , the voice portal  12  may evaluate performance and increase the complexity of the lessons depending on the performance of the user  10 . An exemplary system of the present invention may also recap or summarize the previous sessions if the user  10  is accessing the voice portal  12  after some time interval or if the user  10  requests a review. 
     FIG. 2  shows a dialogue structure that a user may experience when calling the service and initiating an instructional session.  FIG. 2  shows an arrangement or configuration in which the user calls the voice portal  12  and selects, within a dialog setting, the language (for example, “French,” “Spanish” or “German”) and the level (for example, “basic”, “intermediate” or “advanced”). The voice portal  12  recognizes these commands and provides the user  10  with a relevant lesson in the selected language. 
   The flow of  FIG. 2  begins at start  21  and proceeds to action  22 , in which the system initiates the session. The action  22  may include answering a telephone call to the system, and may therefore represent the initiation of contact with the system. The voice portal  12  may answer the phone call or other contact with a greeting of, for example, “Welcome to the Language Learning Center. From your profile I see that you are currently on French level intermediate. Do you want to continue learning French?” Next, in response  23 , the user responds to the interrogatory of the system. If the user responds “yes,” then in action  24 , the system may offer to review the student&#39;s progress by, for example, asking “Do you want to recap your previous session?” After action  24 , in response  25 , the user responds to the interrogatory of the system, and if the user responds “yes,” then in action  26 , the system begins to review the lesson by, for example, “Recapping our previous sessions . . . ” After action  26 , circle  27  may represent the beginning of a review session. If the user responds with a “no” in response  25 , then in action  28  the system begins instruction by, for example, providing the message “Continuing intermediate level French class . . . ” From action  28 , circle  30  may represent the beginning of an instruction session. An example of this instruction session is shown in greater detail in  FIG. 3 . If the user  10  responds with a “no” in response  23 , then in action  29 , the system may interrogate the user  10  by providing the message, for example, “Please select a language, for example, German or Spanish.” After action  29 , in response  31 , the user  10  responds to the interrogatory. If the user  10  responds “German”, then in action  32 , the system interrogates the user  10  by, for example, providing the instructional message “Please select the level of instruction, for example, beginner, intermediate, or advanced.” From action  32 , in response  33 , the user  10  responds to the interrogatory. If the user responds “advanced”, then in action  34 , the system may begin instruction by providing, for example, the message: “Starting advanced level German class.” From action  34 , circle  35  may represent the beginning of an instruction session. Alternatively, in response  31 , the user may respond “Spanish”, which leads to circle  36 , which may represent the beginning of another instructional session. Additionally, in response  33 , the user may respond “beginner”, which leads to circle  38 , or “intermediate”, which leads to circle  39 . Each of circle  38  and circle  39  may represent the beginning of a different instructional session. 
     FIG. 3  shows an exemplary test environment to provide an interactive learning tool for users to aid in improving their language skills in the specified language. Specifically,  FIG. 3  starts with circle  37 , which may represent the same circle  30  from  FIG. 2 , or may represent another starting point. Proceeding from circle  37  to action  40 , the system begins instruction by providing, for example, the message: “Scenario: you meet someone for the first time in a party, how would you greet them, in French.” After action  40 , in response  41 , the user  10  responds. After response  41 , in action  42 , the user response is checked against possible answers. In action  42 , the system may access the database  13 . After action  42 , in action  44 , the system determines a confidence level based on the comparison. Next, at decision-point  45 , the system determines whether the confidence level is equal to or greater than an acceptance limit associated with each possible answer. If the confidence level is greater than or equal to the acceptance limit, then action  46  is performed, which indicates to the system to continue with the next question. After action  46 , circle  47 , may indicate a continuation of the instruction session, including additional scenarios, vocabulary and pronunciation testing, or comprehension skills. 
   If the response at decision-point  45  is negative, which indicates that the confidence level is less than the acceptance limit, then in action  48 , the system informs the user  10  that the response was unsatisfactory. Following action  48 , in question  49 , the system queries whether the user  10  wants to hear a sample correct response. If the user responds affirmatively, then in action  50 , the system provides a sample correct response. Following action  50 , in question  51 , the system queries the user  10  if the question is to be repeated. If the user responds in the negative, then in action  52 , the system prompts the user  10  by providing, for example, the message “Then try again”, and returns to action  41 . 
   If the response to question  49  is negative, then the flow may proceed to question  51 , and if the response to question  51  is affirmative, then action  40  is performed. 
   When the user  10  reaches a certain point in the language course, the system may conduct a test to assess the user&#39;s progress. Depending on the results of the assessment test, the system may recommend whether the user  10  should repeat the lesson or proceed to the next level. 
   Another scenario is that the user  10  may practice by repeating the word until the system recognizes the word, or the system may repeat the word after each attempt by the user  10  to pronounce correctly the word until the user correctly pronounces the word. In the pseudo-classroom, the correction of pronunciation and language nuances may be made immediately by the voice portal. For example, the following dialogue may be part of the language instruction: 
   System: Please say “Telegraphie”&lt;tele&#39;gra:fi&gt; 
   User: &lt;tele&#39;gra: phe&gt; 
   System: That is an incorrect pronunciation, please say it again. &lt;tele&#39;gra:fi&gt;. 
   User: &lt;tele&#39;gra:fi&gt; 
   System: That&#39;s right! Let&#39;s go to the next word. 
   Additionally, the system may test the user  10  in pronouncing groups of words. Term shall mean in the context of this application both single words and groups of words. 
     FIG. 4  shows an exemplary architecture of a combined voice portal  12  and web portal  54 . The user  10  may set a personal profile via a web portal  54 . A geo (geography) server  56  may contain country specific or location specific information, E-mail server  55  may send and receive E-mails in the language being learned, the database  13  may include the user profile, language information and correct and incorrect pronunciations. The voice portal  12  may be the main user interface to learn and practice the language skills. An application server  57  may control access to the geo-server  56 , E-mail server  55  and the database  13  from the voice portal  12  and the web portal  54 . The web portal  54  may be connected to a personal computer  59  via the Internet  60 , or another communication network. The web portal  54  may be coupled or connected to the personal computer  59  via the Internet  60 , or other communication network. The voice portal  12  may be connected or coupled to the telephone  11  (or other communication device) via a telephone system  61 , or other communication network. The geo-server  56 , the E-mail server  55 , the database  13 , the voice portal  12 , the application server  57 , and the web portal  54  may be collectively referred to as a language learning center  58 . Alternatively, the user  10  may access the language learning center  58  without the telephone  11  by using a personal computer  59  having an audio system (microphone and speakers). The user  10  may also access the language learning center  58  without a personal computer  59  by using only the telephone  11 , or some other suitably appropriate communication device. 
   The geo-server  56  may provide location specific information to the user  10  by identifying the location of the user  10  through a GPS system, a mobile phone location system, a user input, or by any other suitably appropriate method or device. The location specific information provided by the geo-server  56  may include the local language, dialect and/or regional accent. For example, the user  10  may call voice portal  12 , and ask the question: “How do I say ‘where can I get a cup of coffee here?” The geo server  56  may locate the user  10  by a mobile phone location system or a GPS system integrated in the telephone  11 . The geo-server  56  may identify the dominant language and any regional dialect for the location of the user  10 . This information may be provided to the application server  57  to assist in accessing the database  13 . Thus, the voice portal  12  may provide the user  10  via telephone  11  with the foreign language translation of the phrase “Where can I get a cup of coffee?” This information may be provided in the local dialect and accent, if any, and the user  10  may then be prompted to repeat the phrase to test the user&#39;s pronunciation skills. 
   E-mail server  55  may be used to send E-mails to the user  10  for administrative purposes (such as, for example, to prompt the user  11  to call the voice portal  12  for a new lesson), or to teach and/or practice reading and/or writing in a foreign language. 
   Voice recognition can be divided into two categories: dictation and dialogue-based. Dictation allows the user to speak freely without limitation. As a consequence, however, voice recognition of dictation may require a large amount of processing power and/or a large set of sound-files/grammar-files, possibly pronounced by the user, to effectively identify the spoken word. There may be few algorithmic limitations on normal speech to aid in the identification of the spoken word, and these limitations may be limited to a few grammar rules. On the other hand, a dialogue-based system may be implemented with less processing power and/or fewer or no sound samples from the user. A dialogue-based system may parse a response into grammatical components such as subject, verb and object. 
   Within each of the parsed components, a dialogue-based system may have a limited number (such as, for example, 15) stored sound files, with each stored sound file associated with a different word. Thus, a dialogue-based system may reduce the level of complexity associated with voice recognition considerably. Additionally, each stored sound file, each parsed grammatical component, or each user response may have an associated acceptance limit, which may be compared to a confidence level determined by the dialogue-based system when associating a particular sound with a particular stored sound file. A high acceptance limit may require a higher confidence level to confirm that the word associated with that stored sound file was the word spoken by the user. This concept may be expanded by using incorrect pronunciation stored sound files. Incorrect pronunciation stored sound files may include the incorrect pronunciation of the word. 
   The system may be designed so that a particular uttered sound does not lead to confidence levels for two different sounds that may exceed the respective acceptance limits for the different stored sounds. In other words, the prompts from the system to the user  10  may be designed so that acceptable alternative responses would have a low possibility of confusion. 
   Limits may be provided by using slots, which may be delimited using recognized silences. For example: 
   
     
       
             
             
           
         
             
                 
                 
             
           
           
             
                 
               “The grass | is | green.” 
             
             
                 
               slot 1  | slot 2 | slot 3 
             
             
                 
                 
             
           
        
       
     
   
   The system may be able to correct the user  10 , if the user  10  uses a wrong word in slot  2 , such as, for example, “are” instead of “is”. There may be other solutions to correct grammatical “ordering” mistakes (such as, for example, “The grass green is.”). The uttered phrase may be compared for one slot with stored phrases associated with other slots for confidence levels that exceed acceptance limits. If any confidence level exceeds an acceptance limit for an uttered phrase compared with a stored phrase for another slot, then an ordering mistake may be identified. The system may then inform the user  10  of the ordering mistake, the correct order and/or the grammatical rule determining the word order. 
   For example, if an answer is expected in the form “You | are | suspicious!” (in which a “|” represents a slot delimiter) and the answer is “Suspicious you are”, then the slots have to have at least the following entries &gt;slot  1 : “you, suspicious”, slot  2 : “are, you”, slot  3 : “suspicious, are” &lt;for the two instances to be recognized. While the combination  111  would be the right one, the system would tell the user  10 , if it recognizes  222 , that the user  10  has made an ordering error. The system may also recognize other combinations as well, such as, for example,  122  if the user stutters,  211 , and other mistakes, and could inform the user  10  as necessary. 
   The application server  57  may manage the call, application handling, and/or handle database access for user profiles, etc. 
   A pool of stored phrases is defined herein as an edition of words recognizable by the system at a given instance, for example “grass, tree, sky, horse, . . . ” For each slot, there can be a different pool of stored phrases. There is an expected diversification of words in each slot, for example: 
   
     
       
             
             
           
         
             
                 
                 
             
           
           
             
                 
               slot 1 | slot 2 | slot 3 
             
             
                 
               The grass is  green. 
             
             
                 
               Is  the grass  green? 
             
             
                 
                 
             
           
        
       
     
   
   A more subject-oriented example may be types of greetings, for example: 
   
     
       
             
             
           
         
             
                 
                 
             
           
           
             
                 
               How are  you? 
             
             
                 
               Nice to meet you! 
             
             
                 
               I have heard so much about you! 
             
             
                 
               Aren&#39;t you  with Bosch? 
             
             
                 
                 
             
           
        
       
     
   
   The speech recognition algorithm may recognize silences or breaks and try to match the “filling” (that is, the uttered phrases) between such breaks to what it finds in its pool of stored phrases. The system may start with recognizing “The”, but since this is not in slot  1 , the system may add the next uttered phrase (“grass”) and try again to find a match, and so on. The developer may need to foresee all possible combinations of answers and feed them into the grammar. Even a whole sentence may be in one slot (such as, for example, a slot representing “yes,” “That is correct!”, “That&#39;s right!”, “Yepp”, etc.) 
   With respect to mispronounced entries, a recognition engine may be capable of handling user-defined stored sounds. In those stored sounds, the mispronounciation must be “defined”, that is, a machine readable wrongly pronounced word must be added (such as, for example, if “car” is the expected word, the pronounciation of “care” or “core” may be used, possibly along with other conceivable mispronunciations). For the system to be able to recognize wrongly pronounced words, those mispronounciations must be known to the system. Otherwise the system may reject them as “garbage” in the best case or interpret them as something else and possibly deliver the wrong error message. 
   Therefore, in operation, the system may provide a scenario to only allow for a few possible subjects, restricted to what is predefined in the pool of stored sounds. 
   If a word is grammatically required, it can be made mandatory, that is, there would be a slot for it (such as, for example, to differentiate between wrong pronounciations or even wrong words). Alternatively, the word can be optional (such as, for example, “Grass is green” or “The grass is green”). If the word is optional, there would be no need to reserve a slot. The word may be marked as optional in the “grass” slot. One way to mark a word as optional would be to use an entry like “?the grass”. The question mark in front of “the” makes it optional for the recognition engine. Different markings for optional words are also possible. 
   An exemplary parsed response is shown in  FIG. 5 . In  FIG. 5 , a “?” in front of words indicates they are optional (other recognition engines accept [ ] or other ways to mark optional words). The system query might be: “Please identify the objects around you with their color!” 
   Valid responses may include: 
   
       
       
         
           The grass is yellow. 
           The grass is green. 
           That big tree is brown. 
           This small cat is yellow.
 
Invalid user responses may include:
 
           That tree is brown. 
           That small dog is yellow. 
         
       
     
  
   The system may reject some responses later on because of context, or language invalidity. For instance:
         The cat is green.   That big tree is blue.       

   In this case, the recognition engine may recognize what the user has said, but the dialogue manager may reject this as an invalid response (although it might be pronounced correctly and semantically correct). 
   In particular,  FIG. 5  shows response  62  divided into slots  63 ,  64 ,  65 ,  68 . Each of slots  63 ,  64 ,  65 ,  66  has at least one associated valid response. For instance, slot  64  has valid responses  67 ,  68 ,  69 ,  70 . Slot  65  has valid response  80 . Valid responses may have one word (such as, for example, valid response  67  has “grass”), or more than one word (such as, for example, valid response  68  has “big tree”). Additionally, valid responses may include optional word delimiters  81 . Optional word delimiter  81  indicates that the word following optional word delimiter  81  in the valid response may be present or may be absent. 
   The exemplary embodiments and methods of the present invention described above, as would be understood by a person skilled in the art, are exemplary in nature and do not limit the scope of the present invention, including the claimed subject matter.

Technology Classification (CPC): 6