YEAH THIRTY YOU CAN SEE YOU C YOU CAN'T REALLY LIKE EVEN YOU CAN'T THE MODELS ITSELF IS LIKE THIRTY EIGHT TIMES MORE THAN THAT SO SO Y IF YOU HAVE LIKE FIVE MEGABYTES OR TEN MEGABYTES OF MODELS THEN YEAH BUT EVEN I THINK IT'S REALLY BIT LIKE IMPOSSIBLE FOR THE REALLY BIG SYSTEMS I GUESS LIKE STORING STORING ITSELF YEAH YEAH YEAH YEAH IT'S REALLY TI YEAH YEAH FOR EVERY YOU'RE SO YOU'RE TO STORE ALL THIS THIRTY AND YOU CANNOT EVEN TRAIN IT RIGHT MORE OR LESS I THINK HMM YEAH THEY TRIED P. C. A. L. D. A. M. L. L. T. OH SO THAT'S INTERESTING I I IT'S NOT REALLY ANYTHING NEW BUT UH THE MM THEY JUST APPLIED THAT TO SPEAKER I. D. YEAH YEAH YEAH SO UH I FOUND ONE PAPER INTERESTING I THINK YOU KNOW VIVEK MOST OF YOU KNOW UH THIS IS UH VIVEK'S PAPER ON LIKE VARIABLE SCALE FEATURE EXTRACTION NORMALLY WE USE TO FIX IT WINDOW FOR FEATURE EXTRACTION LIKE TWENTY FIVE MILLISECONDS OR THIRTY SECONDS HERE HE'S PROPOSING VARIABLE SCALE BECAUSE THE FIXED SCALE IS NON OPTIMAL FOR IT'S NON OPTIMUM BECAUSE LIKE FOR VOWELS YOU CAN HAVE M MUCH LONGER AND FOR PLOSIVES AND THESE THINGS YOU REALLY SHORTER LIKE EVEN AROUND LESS THAN TWENTY MILLISECONDS ALSO SO HE'S KI PROPOSING LIKE THIS VARIABLE SCALE WINDOW F UH KIND OF ONLINE FOR EACH SEGMENT WHY IT HAS TO BE ONLINE YEAH MM MM YOU CAN DO LIKE YOU CAN MEASURE AND YOU CAN DO BUT HE'S MM BASICALLY DOING SOME MM LIKELIHOOD RATIO TESTING SO IF SO THE MAIN IDEA IS LIKE SUPPOSE YOU HAVE UH ONE SEGMENT SO HE'S TRYING TO FIND THE STATIONALITY CAUTIOUS STATIONALITY OF THAT SEGMENT RIGHT LIKE EXTENDED AS AS MORE AS MUCH AS POSSIBLE TO KEEP THE OKAY OF COURSE OF COURSE WH WHAT IS THE MINIMUM AND MAXIMUM MAXIMUM IS UH SIXTY MILLISECONDS SO IT'S NOT SO MM SO THE MINIMUM WHOO YEAH IT'S RIGHT TWENTY MILLISECONDS FROM OH YEAH IT'S NO NOT AS SMALL AS AS IT SHOULD HAVE BEEN BUT MAYB MAYBE BECAUSE OF OTHER PROCESSING AFTER NO YEAH WELL NOISY YES TEN MILLISECONDS MEANS YOU HAVE ONLY EIGHTY SAMPLES FOR UH AND THEN YOU HAVE REFUSED TWENTY FOUR FILTERS THE FILTERS WON'T GET ANY SAMPLES SO BUT IT'S NOT UH AN INTRINSIC LIMITATION IT'S JUST BECAUSE OF RI YEAH OKAY AND THE SHIFTING IS STILL THE SAME OR NOT SHIFTING YEAH HE'S USING TWELVE POINT FIVE MILLISE YEAH SHIFTING IS ALMOST SAME BUT THE PROBLEM LIKE LIKE UM NO HOW MANY FRAMES PER PER SECOND YOU DO HAVE IS IT AGAIN LIKE UH ONE HUNDRED FRAMES OR IT'S LESS OR EVEN IF YOU KEEP VARIABLE LENGTH OF THE FRAMES RIGHT YOU CAN STILL KEEP THE SAME FRAME RATE UH HE'S USING UH TWELVE POINT FIVE YEAH TWELVE POINT FIVE MILLISECOND RIGHT BUT WHY DO WHY TO DO IT FOR SPEECH RECOGNITION IT MEANS THAT UH NUMBER OF UH FRAMES W YOU WANT TO WH WHY NOT TO KEEP THE SAME LENGTH WHAT IS THE YEAH SO AGAIN IF YOU CHANGE THIS SHIFT THE MOD THE NYQUIST THE MODULATION SPECTRUM NYQUIST FREQUENCY CHANGES FOR EACH WINDOW SO IF YOU WANT TO DO AGAIN ANOTHER HIGH LEVEL FEATURE EXTRACTION AGAIN IT WILL BE PROBLEM SO SO BUT HE'S UH LIKE HE'S HE DISCUSS I MEAN DESCRIBING THIS BECAUSE EVEN THIS ITSELF IS A PROBLEM KEEPING THE F UH FIX TO FRAME SIZE BECAUSE YOU'RE ANALYSING YOUR THIS UH SEGMENT MANY TIMES RIGHT RIGHT RIGHT MM-HMM MM UH YEAH FIVE FRAMES Y YOU'RE ANALYSING THE PREVI THIS ALREADY SEGMENT SO SO AGAIN THIS MAY BLUR SOME FREQUENCY TRANSITIONS OR YEAH BUT THE PROBLEM IS AGAIN THIS UH BOTTLENECK IS HERE LIKE YOU CAN'T CHANGE YOUR NYQUIST FREQUENCY MODULATION AND UM I HAVE TWO QUESTIONS FIRST IS ESSENTIALLY HOW HE'S DOING IN THAT NO WELL UH ONCE HE GETS THE FRAME LIKE FROM HERE TO HERE THEN WHERE HE ADVANCES TO TO START WITH C COMPUTATION OF THE NEXT FRAME SO IT'S SO UH SO THE MAIN IDEA IS LIKE FIRST TO TAKE THE SOME SOME WINDOW SOME SAM SOME SAMPLES THEN HE ASSUME SOMEWHERE SOME VARIABLE AND POINT THERE IS A CHANGE OKAY SO IT'S NOT N IT'S NOT SYMMETRIC NECESSARILY 'KAY SO THEN WHAT HE DOES IS LIKE HE PROPOSED UH LIKE SOME LIKE RATIO TEST BASED ON MAXIMUM LIKELIHOOD SO TH THA THAT IS REALLY SIMPLE LIKE SO WHAT HE DOES IS LIKE SO HE HE COMPUTES THE RESIDUAL HE FIRST HE DOES THE L. P. ANALYSIS AND THEN HE COMPUTES THE RESIDUAL AND HE TAKES THE RESIDUAL ENERGY OF F FULL SIGNAL LIKE GY GY GYRO SAMPLES THE FULL SIGNAL SO MAYBE I CAN THE WH THE WHOLE WINDOW NO THAT'S THAT LIKE HE ASSUMES YEAH SIXTY MILLISECONDS OR SOMETHING HE START WITH SO SO THEN HE CAN YEAH YEAH YEAH THEN HE CAN SPLIT THAT WINDOW AT POINT N. SAY POINT N. SO THEN YOU WILL HAVE GYRO TWO NO YOU CAN SEGMENT IT MAYBE YEAH SO YES HE'S SUPPOSED THIS IS YOUR P WINDOW SO THEN YOU CAN MOVE YOUR LIKE THIS YOU CAN MOVE YOUR POINT SO THAT THEN THIS WILL BE LIKE ONE AND THIS WILL BE SECOND BUT AGAIN HE ASSUMES SOME INITIAL UH SIZES FOR THESE WINDOWS OKAY SO BASICALLY WE HAVE TWO FIXED POINTS HE'S STARTING WITH UH SO THE L LEFT WINDOW IS STARTS AT TWENTY MILLISECONDS SO SO YOU ALREADY HEAR LIKE S SUPPOSE THIS IS FULL SIGNAL YOU'RE ALREADY HERE SO RIGHT WINDOW IS SHOULD END AT TWELVE POINT TWO SO YOU'RE TO SEARCH BASICALLY IN THIS RANGE SO YEAH YEAH YEAH AND THEN IF YOU THE MAXIMUM IS SIXTY MILLISECOND FRAME FOR HIM SO IF YOU DON'T FIND ANYTHING WHERE WHERE DO YOU STOP ACTUALLY YEAH MM I KNOW BUT YOU START AT TWENTY AND GO TO SIXTY BUT WHERE WHICH POINT DO YOU CHOOSE NO THE POINT IS DEPENDING ON THE LIKELIHOOD RATIO SO HE GOT SO HE SUPPOSED THIS SO THIS IS SUPPOSE SE SEGMENT ONE AND THIS IS SEGMENT TWO SO HE COMPUTE THIS ERROR HERE SO AND THEN HE P GIVES SOME KIND OF IN TERMS OF THIS RESIDUAL LETTER SO THIS RESIDUAL LETTER IS FOR FULL GYRO SAMPLES THEN THERE WOULD BE SUPPOSE THIS POINT IS SAY N. SO GYRO TO N. AND THEN LIKE SO THIS THE B BASICALLY THE MAIN HE QUESTIONS OR HERE YEAH HE'S FOR FINDING THE LIKELIHOOD FOR FULL FRAME AND THEN IT'S BASICALLY LIKELIHOOD RATIO TEST SO HE'S COMPARING THE LIKELIHOOD OF THE FULL SEGMENT DIVIDED BY THE LIKELIHOOD OF THE THE SUB SEGMENTS W WHAT IS LIKELIHOOD OKAY SO RESIDUAL POWER HE CAN COMPARE T SO HE AFTER DO AFTER DOING L. P. HE CAN GET A L RESIDUAL AND THEN HE CAN COMPARE THE POWER OF THE RESIDUAL SO THAT HE'S PROVING THAT POWER IS AGAIN MAXIMUM LIKELIHOOD ESTIMATE OF YOUR L. P. PARAMETERS SO THAT WHICH INTERESTING IT'S YOU DON'T REALLY NEED TO DO A LOT OF COMPUTATION