Automated speech translation system using human brain language areas comprehension capabilities

Abstract

The present invention is an “Automated Speech Translation System using Human Brain Language Areas Comprehension Capabilities”. It discloses a method to address the most common variation in the world, which is communication gap between people of different ethnicity. Imagine a world where we can communicate with our natural language to everyone without the need of human translators, interpreters, hand-held device and language translation books. In order to facilitate language translation, this present invention recognizes the speech in voice pitches, collects the language comprehensive information from each recipient's brain language areas within the audible range and sends it to “voice processing center” for analyzing. Then, it translates the collected voice pitches of speech to natural language of recipient(s) by using language dictionaries database. The translated language is retransmitted in audible frequency to one or plurality of recipients where the brain language areas of one or plurality of recipients can comprehend.

1. A speech translation system to translate a speech originating from a source entity into a speech that can be understood by other entities' brain language areas,
 wherein said a source entity is a human being;  
 wherein said the other entities are human beings; 
 wherein said the brain language areas are nerve cells in a human brain's Left hemisphere and Right hemisphere, 
 wherein said Right hemisphere is an region located in the frontal lobe usually of the left cerebral hemisphere and associated with the motor control of speech,  
 wherein said Left hemisphere is an area in the posterior temporal lobe of the brain involved in the recognition of spoken words;  
 
 
 said speech translation system comprising: 
 a Voice Processing Center.  
 
 
     
     
       2. The speech translation system according to  claim 1 , wherein a Voice Processing Center for handling the speech signals analyses and determining the natural language of one or plurality of said entities who are listening to the speech of said source entity,
 wherein said process the speech signals analyses are processing the signals in a digital representation.  
 
     
     
       3. A method to broadcast the signals for collecting the voice pitches consisting of alternating high and low air pressure travelling through the air and direct the signals towards the said other entities head to collect rapid analysis of the said brain language areas while listening to the speech of said source entity,
 wherein said rapid analysis of the said brain language areas is the analysis of brain language areas activities while hearing the speech of said source entity.  
 
     
     
       4. A method according to  claim 3 , comprising:
 an Intelligent Natural Language Program where it travels over the air and looks for an voice pitches consisting of alternating high and low air pressure travelling through the air and collecting the said brain language areas comprehension characteristics of said other entities' who are all in the audible range of said the voice pitches consisting of alternating high and low air pressure travelling through the air, said an intelligent natural language program comprising: 
 an intelligent speech recognition algorithm identities an acoustic waveform consisting of alternating high and low air pressure travelling through the air and recognizes the phoneme-level sequences from an acoustic waveform;  
 a Language Area Acquisition Algorithm collects said language areas comprehensive information from the said brain language areas of said other entities said who are in audible range of speech of a said source entity.  
 
 
     
     
       5. A method to isolate the phoneme-level sequences, and rapid analysis of the language comprehension of said brain language areas of one or plurality of said entities, from received signal. 
     
     
       6. A method to determine the natural language of intended one or plurality of said entities using collection of human said brain language areas comprehension characteristics,
 wherein said human brain language areas comprehension characteristics are the digital data representation of human said brain language areas activity while hearing any audible speech.  
 
     
     
       7. A method according to  claim 6 , comprising:
 a Language Area Inference Engine is a routine that derives natural language information from the collection of Human Brain Language Areas Comprehension characteristics.  
 
     
     
       8. The speech translation system according to  claim 7 , wherein said Language Area Inference Engine to identify the natural language from received language area comprehensive analysis, said Language Area Inference Engine further comprising:
 a “Human Brain Language Areas Knowledge Base” is the collection said Human Brain Language Areas Comprehension characteristics;  
 a routine to Identify Natural Language from received language area comprehensive analysis;  
 the Natural Languages Cache database is a collection of identified natural languages data.  
 
     
     
       9. The speech translation system according to claims, wherein said “Human Brain Language Areas Knowledge Base” is an exhaustive, comprehensive, obsessively massive list of brain samples of language areas activity information; wherein said the list of samples are collected information from experimental test results data of brain's language areas activities and collected information from neurologists about brain's language areas comprehension, said “Human Brain Language Areas Knowledge Base” comprises of plurality of brain data collected by recording the brain language area activity for each of the natural language spoken around the world. 
     
     
       10. The speech translation system according to  claim 8 , wherein said Natural Languages Cache database is a temporary storage area of identified natural languages to frequently access the natural language data said Natural Languages Cache database used for further said natural language identification method by accessing the cached copy rather than re-fetching or recomputing the original natural language data. 
     
     
       11. A method to translate the speech sentence of said source entity in natural language of said source entity into a speech sentence of natural language of said other entities, wherein said natural language is the language a human being learns from birth. 
     
     
       12. A method according to  claim 11 , comprising:
 a Speech Translation Module for building the information content with grammatical rules of the natural language from received phoneme-level sequences, and translate to identified natural languages which said identifying the natural languages from language area comprehensive information by said language area inference engine, wherein said translate is translating built information content to said natural languages identified by said language area inference engine using language dictionaries, said Speech Translation Module comprising: 
 a parser to activate a hypothesis as to the correct phoneme sequence from the elliptical, ill-formed sentences that are appeared in the speech;  
 an information extractor to form a sentence from phoneme-level sequences;  
 a phrase/word translator is closely integrated with Language Inference Engine and Language dictionaries to translate words of source entity into words in natural languages of other entities;  
 a generation module integrated with said phrase/word translator in order to generate the most specific expressions using past cases and their generalization, while maintaining syntactic coverage of the generator;  
 a speech synthesizer connected to said output of said generation module so as to broadcast audible speech which is the translation of said spoken words in said target language.  
 
 
     
     
       13. The speech translation system according to  claim 12 , wherein said language dictionaries is an exhaustive, comprehensive, obsessively massive dictionaries of all words from each of the natural languages spoken around the world, said the language dictionaries are used for translating the spoken word to any of the other natural languages, steps of building said the language dictionaries:
 collecting words and set of grammatical rules presents in each natural language spoken in the world;  
 storing the words alphabetically, with definitions, etymologies, phonetics, pronunciations.  
 
     
     
       14. A method to identify the natural language of one or plurality of said entities using said brain language areas of each said entity, said method comprising the steps of:
 directing said Language Areas Acquisition signal towards one or plurality of said entities while listening to the speech of said source entity;  
 collecting rapid analysis of the brain language areas activity of one or plurality of said entities while listening to the speech of said source entity;  
 decoding the language comprehension features from the said collected brain language areas rapid analysis;  
 selecting the identical said language comprehension features of brain language areas from said “Human Brain Language Areas Knowledge Base” by comparing language comprehension features of said collected brain language areas rapid analysis characteristics with entries in said “Human Brain Language Areas Knowledge Base”;  
 selecting the equivalent name of natural language information for matched entry of said “Human Brain Language Areas Knowledge Base” when identical language comprehension features of said brain language areas rapid analysis are matched with one of the entry in said “Human Brain Language Areas Knowledge Base”.  
 
     
     
       15. A method to build the “Human Brain Language Areas Knowledge Base” by collecting the massive store house of characteristics of brain language areas comprehension for all natural languages spoken across the world, said method comprising the steps of:
 presenting an audible speech in particular natural language presented to a human being for whom particular natural language is the language he/she learns from birth;  
 connecting the materials to the language areas of a human being's brain to make contact with the neurons of said language areas of his/her brain during the experiment, 
 wherein said materials are the electrodes used to make contact with the neurons of brain;  
 
 recording said a human being's brain language areas activity while listening to the audible speech in a particular natural language;  
 translating the recorded said brain language area activity signals using a translator that uses algorithms to decode the recorded signals said in step of recording brain language areas activity to determine the characteristics of the particular natural language;  
 storing the test results along with name of the natural language information in the said “Human Brain Language Areas Knowledge Base”; said steps of building the “Human Brain Language Areas Knowledge Base” are executed repeatedly with human beings for all natural languages spoken in the world.  
 
     
     
       16. A method to allow the said entities to comprehend the language spoken by said other entities wherein comprehend said brain language areas comprehend, said method comprising the steps of:
 recognizing voice pitches consisting of alternating high and low air pressure travelling through the air, originating from a said source entity and identifying the phoneme-level sequences by said an intelligent speech recognition algorithm of said Intelligent Natural Language Program;  
 identifying the said other entities who are all in the audible range of said voice signal originating from a source;  
 directing said language areas acquisition signal towards brain language areas of said other entities;  
 collecting rapid analysis of said brain language areas comprehensive information of said other entities;  
 analyzing phonemes and rapid analysis of said brain language areas comprehension of said other entities in said voice processing center;  
 identifying the said natural language of said entities by comparing received language areas comprehension features of brain language areas of said entities with said “Human Brain Language Areas Knowledge Base”;  
 identifying the said natural language of phoneme-level sequence of speech of said source entity;  
 translating the spoken sentence of said source entity in to one or plurality of said natural languages identified in said step identifying the natural language;  
 broadcasting said each translated sentence with a said voice synthesizer to one or plurality of intended said entities.