OKAY OKAY YES UM SO YOU WERE TALKING ABOUT THE TWO FIRST QUESTION OKAY AND A LITTLE BIT ABOUT SAME PEOPLE MOVING WITH THE CLUSTERING AND THIS ALSO UM ALLOWS YOU TO SEPARATE PEOPLE UH-HUH UM AND THE QUESTIONS I DID NOT TALK ABOUT WAS UH GOING FROM LOCATION TO UH IDENTITY OF THE PERSON UM THAT IS QUITE DIFFERENT YOU YOU NEED TO USE A SIGNAL YOU HAVE SEPARATED AND UH DO THE TYPE OF ANALYSIS I MENTIONED UM FROM THE SPECTRUM YOU CAN TRANSFORM THE THE MAGNITUDE SPECTRUM AND UM UM BUILD MODEL OF THE PERSON MM-HMM OR ACTUALLY LOOK AT THE PITCH NO DON'T ASK ME HOW IT'S DONE I I KNOW THE THEORY SO YEAH ISN'T IT THE PITCH AND THE FREQUENCY THE BASE FREQUENCY OF THE IT'S A FREQUENCY OF YOUR VIBRATION HERE UH YEAH AND THEN IT'S TRANSFORMED THROUGH THE MOUTH THAT'S THE USUAL MODEL AND IF YOU HAVE BOTH YOU CAN UM WELL YOU CAN COMPARE THIS TO TO ONE STORED AND SO GET OUT UH WHICH PERSON IT IS PARDON WHAT AND UH WELL THE THINGS THAT MAKE THE SOU THE VOICE OR SO AGAIN F. F. T. IS USEFUL TO DO THIS TYPE OF ANALYSIS UM YEAH BUT IT'S QUITE PERSONAL UH YEAH YOU WERE COMPARING WHAT WITH WHAT UH-HUH OKAY OKAY AND THAT'S THAT'S REALLY UH UNIQUE FOR EV WELL ALMOST UNIQUE FOR EVERY PERSON SO WELL ONCE YOU GET THIS INFORMATION YOUR FREQUENCY AND UH YOUR VOCAL CONTRACT OR HOW IT'S CALLED UH Y YOU CAN USE THIS INFORMATION TO COMPARE TO TO TO THE FRAMES HERE IT IT'S AN INFORMATION EQUIVALENT TO THAT IT'S MAYBE N YOU DON'T NEED TO DO THE WHOLE UH COMPLICATED MODELLING BUT NO NO NO NO THAT THAT THAT EVERYTHING IS DONE THROUGH THROUGH THE VOICE HERE YOU TAKE A VOICE OF SOMEONE AND THEN YOU CAN GET OUT THIS INFORMATION IT'S IT'S NOT P IT'S CLEAR IT'S NOT PERFECT BUT S IT'S ENOUGH TO TO TO USE IT FOR FOR DIFFERENT PURPOSES AND UH YEAH RATE OF SPEECH IS ALSO POSSIBILITY UM HOW FAST YOU SPEAK THAT'S QUITE PERSONAL ALSO BUT IT VARIES OVER TIME UM DEPENDING ON EMOTION THAT ALSO MIGHT BE INTERESTING FOR YOU DETECTING EMOTION EMOTION THE INVOLVEMENT IN A DISCUSSION IF YOU ARE SAYING OH YEAH YEAH WE SHOULD OKAY IN C. P. U. YOU MEAN NO NO IT'S NOT BUT IN FACT IF Y YOU SPEAK OF UH A LOT OF THINGS THAT ARE NOT EXPENSIVE AT THE END YOU HAVE UH SOMETHING THAT IS SO YOUR DECISION CAN BE FOR EXAMPLE UH WHO IS IT OR IF THE PERSON MOVED WHICH IS PROBABLY THE MOST COMPLICATED THING LIKE THE PERSON GOES AWAY THEN COMES BACK TEN MINUTES LATER SITS AT A DIFFERENT PLACE UH YOU WILL NEED TO BUILD STATISTICAL MODELS OF UM THE PERSON IDENTITY USING THESE MEASURES SO THE ONES UM HE MENTIONED UM I DON'T KNOW IF YOU'RE FAMILIAR WITH THAT IS IT CALLED P. C. M. I THI UM WELL IT'S IT'S NOT A TECHNOLOGY S YEAH IT'S MORE OR LESS USED THIS TO COMPRESS AUDIO I HAVE TO I WANT TO CHECK IT I CAN SHOW IT YOU AFTERWARDS SO UM NOT REALLY FAMILIAR WELL I DID A COURSE ABOUT IT BUT UH I SHOULDN'T SAY IT TOO LOUD BECAUSE UM THE PROFESSOR IS WORKING HERE AT IDIAP I SHOULD REREAD WHAT I SIGNED THERE SO YEAH SO YOU HAVE TO DO F. F. T. BECAUSE OTHERWISE ALSO LOCATION TO IDENTITY UH ALL I WAS SAYING IS THAT THESE DIFFERENT MEASURES ARE A WAY TO UH EVALUATE THE IDENTITY OF THE PERSON SO IF WITH LOCATION ALL YOU CAN DO IS EXTRACT SEGMENTS OF SPEECH FOR EXAMPLE BUT IT WILL NOT TELL YOU THAT THESE ARE THE SAME PERSON IT'S JUST A LOCATION YEAH YEAH YEAH SO THAT MIGHT BE GOOD FOR EXAMPLE FOR TEN MINUTES BUT THEN THE PERSON MIGHT MOVE OR A DIFFERENT PERSON MIGHT COME BUT FOR INSTANCE FOR A SETTING LIKE UH HERE IT WOULD BE ENOUGH BECAUSE WE ARE NOT MOVING IT IS WELL UNLESS SOMETIMES SOMEBODY GOES THERE OR YEAH YES BUT WE ARE UH TARGETING A PLACE WHERE WE DON'T KNOW I WHERE IT WILL BE MORE FLEXIBLE SO WE NEED MORE THAN JUST UH LOCATION IF WE WANT TO UH YES BUT IT MM-HMM OR SO SOMETHING UH PHYSICAL UH YOU JUST WANT TO KNOW IN IN WHICH CORNER OF THE TABLE UH SPEECH IS COMING AND NOT UH WHICH PERSON PRODUCED THE SPEECH SO BECAUSE UH IF YOU SAY UH LET'S SAY UH W HOW MUCH THE PERSON UM HAVE SPOKEN OVER THE THE FIVE LAST MINUTES UH SO IT HMM UH IF SOMEONE COME AND YES BUT THAT YOU CAN DO WITH LOCATION IF IT'S ONLY ON THE SHORT TERM YES YES Y ON ON THE OFF LINE YEAH I WOULD SAY YOU MIGHT USE THESE MEASURES IN A SIMPLE WAY IF YOU DO IT UH ON LINE LIKE UM TO GIVE FEEDBACK BUT UH YOU YOU MENTIONED THAT ANOTHER SIDE OF YOUR PROJECT IS ALSO TO ANALYSE OFF LINE SO THERE YOU MIGHT WANT TO USE A THIS IS UH MM AND HIS SOFTWARE IS PRECISELY TO DO THAT TO UM CLUSTER AT UH ANOTHER LEVEL TO CLUSTER THESE SMALL CLUSTERS OF SPEECH UH GROUP THEM BY PERSON AUTOMATICALLY Y NO FROM THE THESE MEASURES PITCH ETCETERA OKAY SO I UH THIS IS ONLY BASED ON UH YOU GIVE UH THE SPECTRUM AND UH UH OKAY SO I WOULD SAY FROM LOCATION AT THE LOWER LEVEL YOU CAN GET SMALL PARTS OF SPEECH AND THEN AT THE NEXT LEVEL POSSIBLY OFF LINE YOU CAN UH GROUP THEM INTO UM A SPEECH SEGMENT I'M HOPING TO HAVE ENOUGH TIME TO TRY UM DOING THAT BEFORE I FINISH MY THESIS UM SO IF I MANAGE TO DO SOME UM UH PRACTICALLY USABLE SOFTWARE I'LL TELL YOU MM-HMM WHEN ARE YOU PLANNING TO FINISH YOUR UH IN FIVE SIX MONTHS ABOU APPROXIMATELY BUT UH THE LAST ONES ARE ALWAYS THE MORE EXTENSIBLE MM NOT REALLY MORE BUSY I WOULD SAY YEAH SO YOU SAID YOU WANT TO DO SEPARATION UM BUT EX EXACTLY YEAH YEAH OKAY OKAY HMM UH I I SAID UH WE WANT T TO KNOW TO UM TO DO SEPARATION JUST BECAUSE OF THE VOICE RECOGNITION I MM THIS IS NOT THE YES YES NO BUT BUT IN FACT WE HAVE UH YES WE ARE DESIGNING UH A NOISE SENSITIVE TABLE JUST F FROM YOUR RING BUT WE ARE ALSO DESIGNING UH A PROTOTYPE UM TO ANALYSE THE CONVERSATIONS SO UH WE MIGHT ADD THERE A LOT OF UH FEATURES SO YEAH ONCE YOU HAVE LOCATIONS IT'S NOT A BIG PROBLEM UM MM-HMM UH I DON'T KNOW IF UH VOICE RECOGNITION OF AN UH SUCH A STREAM IS UH REAL OKAY SO YES SO THAT'S FINE SO THE TYPE OF THINGS I PRESENTED CAN LEAD TO SEPARATION SURE UM IT'S ONLY A VERY SMALL STEP TO ADD YES IT'S NOT UM EVERY IMPORTANT FEATURE FOR NOW BUT YEAH YEAH