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ESPnet2 pretrained model, Hoon Chung/librispeech_asr_train_asr_transformer3_dist_raw_bpe_sp_valid.acc.ave, fs=16k, lang=en

Authors: Chung, Hoon;

ESPnet2 pretrained model, Hoon Chung/librispeech_asr_train_asr_transformer3_dist_raw_bpe_sp_valid.acc.ave, fs=16k, lang=en

Abstract

This model was trained by Hoon Chung using librispeech recipe in espnet. Python API See https://github.com/espnet/espnet_model_zoo Evaluate in the recipe git clone https://github.com/espnet/espnet cd espnet git checkout 991f5a1801a23bb1a269c8718e3cb8e66cb42be5 pip install -e . cd egs2/librispeech/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model Hoon Chung/librispeech_asr_train_asr_transformer3_dist_raw_bpe_sp_valid.acc.ave Results # RESULTS ## Environments - date: `Tue Sep 8 15:22:43 KST 2020` - python version: `3.7.7 (default, May 7 2020, 21:25:33) [GCC 7.3.0]` - espnet version: `espnet 0.9.2` - pytorch version: `pytorch 1.5.0` - Git hash: `991f5a1801a23bb1a269c8718e3cb8e66cb42be5` - Commit date: `Fri Sep 4 18:43:28 2020 +0900` ## asr_train_asr_transformer3_dist_raw_bpe_sp ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_asr_model_valid.acc.ave/dev_clean|2703|54402|97.5|2.3|0.2|0.3|2.8|33.3| |decode_asr_asr_model_valid.acc.ave/dev_other|2864|50948|93.3|6.0|0.6|0.8|7.4|53.2| |decode_asr_asr_model_valid.acc.ave/test_clean|2620|52576|97.3|2.5|0.2|0.4|3.1|34.3| |decode_asr_asr_model_valid.acc.ave/test_other|2939|52343|93.4|6.0|0.6|0.9|7.5|56.0| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_asr_model_valid.acc.ave/dev_clean|2703|288456|99.3|0.4|0.3|0.3|1.0|33.3| |decode_asr_asr_model_valid.acc.ave/dev_other|2864|265951|97.5|1.5|1.0|0.8|3.3|53.2| |decode_asr_asr_model_valid.acc.ave/test_clean|2620|281530|99.3|0.4|0.3|0.3|1.0|34.3| |decode_asr_asr_model_valid.acc.ave/test_other|2939|272758|97.7|1.4|1.0|0.9|3.2|56.0| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_asr_model_valid.acc.ave/dev_clean|2703|69307|96.9|2.1|1.0|0.5|3.6|33.3| |decode_asr_asr_model_valid.acc.ave/dev_other|2864|64239|92.0|5.7|2.3|1.2|9.2|53.2| |decode_asr_asr_model_valid.acc.ave/test_clean|2620|66712|96.6|2.2|1.1|0.4|3.8|34.3| |decode_asr_asr_model_valid.acc.ave/test_other|2939|66329|91.9|5.5|2.6|1.1|9.1|56.0| ASR config config: conf/tuning/train_asr_transformer3_dist.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_asr_transformer3_dist_raw_bpe_sp ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 dist_backend: nccl dist_init_method: file:///SPL37/bin/hspnet/egs2/librispeech/asr1/exp/asr_train_asr_transformer3_dist_raw_bpe_sp/.dist_init_1e12e791-4bcb-4413-95ea-9445becdf71e dist_world_size: 32 dist_rank: 0 local_rank: 0 dist_master_addr: null dist_master_port: null dist_launcher: null multiprocessing_distributed: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 60 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - acc - max keep_nbest_models: 10 grad_clip: 5.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 1 no_forward_run: false resume: true train_dtype: float32 use_amp: false log_interval: null pretrain_path: [] pretrain_key: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 120000000 valid_batch_bins: null train_shape_file: - exp/asr_stats_raw_sp/train/speech_shape - exp/asr_stats_raw_sp/train/text_shape.bpe valid_shape_file: - exp/asr_stats_raw_sp/valid/speech_shape - exp/asr_stats_raw_sp/valid/text_shape.bpe batch_type: numel valid_batch_type: null fold_length: - 80000 - 150 sort_in_batch: descending sort_batch: descending multiple_iterator: false chunk_length: 500 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 train_data_path_and_name_and_type: - - dump/raw/train_960_sp/wav.scp - speech - sound - - dump/raw/train_960_sp/text - text - text valid_data_path_and_name_and_type: - - dump/raw/dev/wav.scp - speech - sound - - dump/raw/dev/text - text - text allow_variable_data_keys: false max_cache_size: 0.0 valid_max_cache_size: null optim: adam optim_conf: lr: 0.002 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 token_list: - - - "\u2581THE" - S - "\u2581AND" - "\u2581OF" - "\u2581TO" - "\u2581A" - "\u2581IN" - "\u2581I" - "\u2581HE" - "\u2581THAT" - T - E - "\u2581WAS" - ED - "\u2581IT" - '''' - "\u2581HIS" - D - ING - "\u2581YOU" - "\u2581AS" - "\u2581FOR" - "\u2581WITH" - "\u2581HAD" - "\u2581HER" - "\u2581" - "\u2581IS" - "\u2581BE" - A - "\u2581NOT" - "\u2581BUT" - "\u2581SHE" - N - "\u2581AT" - I - "\u2581ON" - LY - R - Y - "\u2581HAVE" - O - "\u2581HIM" - "\u2581THEY" - "\u2581BY" - "\u2581ALL" - M - "\u2581THIS" - "\u2581WHICH" - "\u2581FROM" - "\u2581MY" - "\u2581WE" - "\u2581ME" - "\u2581SO" - "\u2581ONE" - "\u2581WERE" - L - "\u2581AN" - "\u2581THERE" - "\u2581SAID" - "\u2581OR" - ER - "\u2581NO" - "\u2581ARE" - "\u2581WHEN" - "\u2581IF" - "\u2581WOULD" - "\u2581THEIR" - "\u2581WHO" - "\u2581OUT" - "\u2581THEM" - "\u2581BEEN" - "\u2581UP" - "\u2581WHAT" - G - "\u2581WILL" - "\u2581DO" - IN - P - "\u2581MAN" - "\u2581THEN" - C - "\u2581MORE" - "\u2581COULD" - "\u2581INTO" - "\u2581YOUR" - "\u2581NOW" - 'ON' - "\u2581SOME" - B - H - "\u2581CAN" - "\u2581HAS" - "\u2581LIKE" - "\u2581LITTLE" - "\u2581VERY" - "\u2581TIME" - "\u2581ABOUT" - OR - AL - RE - "\u2581OVER" - LL - "\u2581OUR" - "\u2581THAN" - F - "\u2581UPON" - "\u2581ONLY" - "\u2581DID" - U - K - "\u2581SEE" - "\u2581TWO" - IT - "\u2581ANY" - "\u2581WELL" - "\u2581DOWN" - "\u2581DE" - "\u2581GO" - "\u2581BEFORE" - "\u2581ITS" - "\u2581OTHER" - "\u2581KNOW" - "\u2581GOOD" - "\u2581US" - "\u2581AFTER" - AN - V - "\u2581MADE" - IS - "\u2581OLD" - "\u2581MUST" - "\u2581SHOULD" - VE - "\u2581HOW" - "\u2581WHERE" - "\u2581COME" - "\u2581WAY" - "\u2581GREAT" - "\u2581DAY" - "\u2581HERE" - "\u2581MISTER" - "\u2581SUCH" - "\u2581NEVER" - "\u2581CAME" - "\u2581MUCH" - "\u2581RE" - "\u2581AM" - "\u2581BACK" - "\u2581MEN" - "\u2581THESE" - "\u2581MAY" - W - "\u2581FIRST" - "\u2581LONG" - ATION - NESS - "\u2581TOO" - "\u2581OWN" - "\u2581UN" - "\u2581THINK" - TH - "\u2581LIFE" - "\u2581AGAIN" - "\u2581JUST" - "\u2581HAND" - "\u2581EVEN" - "\u2581HIMSELF" - "\u2581SAY" - "\u2581DON" - "\u2581THROUGH" - "\u2581MIGHT" - ITY - "\u2581THOUGHT" - AS - "\u2581MAKE" - "\u2581FACE" - "\u2581EYES" - LE - ABLE - "\u2581MOST" - "\u2581THOSE" - "\u2581WENT" - "\u2581TAKE" - "\u2581AWAY" - "\u2581EVERY" - "\u2581WHILE" - "\u2581LAST" - "\u2581STILL" - "\u2581OFF" - X - "\u2581GET" - "\u2581NIGHT" - "\u2581BEING" - US - "\u2581HOUSE" - "\u2581WITHOUT" - "\u2581MANY" - "\u2581SHALL" - ENT - "\u2581UNDER" - TED - "\u2581HEART" - "\u2581YOUNG" - "\u2581YET" - "\u2581HEAD" - "\u2581FOUND" - UR - "\u2581ROOM" - "\u2581LET" - "\u2581NEW" - "\u2581ONCE" - "\u2581THOUGH" - "\u2581RIGHT" - "\u2581PEOPLE" - "\u2581TELL" - "\u2581NOTHING" - "\u2581PLACE" - "\u2581WORK" - ERS - "\u2581EVER" - "\u2581THREE" - AT - OUS - TER - "\u2581FATHER" - "\u2581SAW" - IC - EST - "\u2581GIVE" - CH - "\u2581MOMENT" - "\u2581LOVE" - "\u2581MIND" - "\u2581ANOTHER" - MENT - "\u2581LOOK" - "\u2581LOOKED" - "\u2581PART" - LING - "\u2581MISSUS" - "\u2581LIGHT" - "\u2581LEFT" - "\u2581SAME" - "\u2581FAR" - "\u2581HOME" - "\u2581WORLD" - "\u2581SIDE" - "\u2581PUT" - "\u2581MA" - "\u2581SEEMED" - "\u2581GOD" - Z - "\u2581GOT" - MAN - "\u2581GOING" - "\u2581THINGS" - "\u2581WHY" - "\u2581DOOR" - RY - "\u2581TOOK" - "\u2581END" - "\u2581C" - "\u2581ALWAYS" - "\u2581FEW" - "\u2581MOTHER" - "\u2581DIS" - "\u2581SOMETHING" - "\u2581MISS" - "\u2581CON" - "\u2581KNEW" - "\u2581THING" - "\u2581WOMAN" - ANT - "\u2581LA" - TING - ATE - "\u2581WANT" - "\u2581TOLD" - "\u2581AGAINST" - "\u2581HEARD" - "\u2581BECAUSE" - "\u2581HALF" - "\u2581YEARS" - "\u2581FIND" - "\u2581SIR" - "\u2581WATER" - VER - CK - ATED - "\u2581VOICE" - "\u2581NAME" - "\u2581BETTER" - "\u2581EACH" - ISH - "\u2581ENOUGH" - FUL - LESS - IES - UL - LED - "\u2581QUITE" - "\u2581SEEN" - AGE - GE - IVE - "\u2581CAR" - "\u2581DONE" - "\u2581SOON" - "\u2581HANDS" - ANCE - "\u2581BOTH" - "\u2581WHITE" - "\u2581COURSE" - "\u2581TURNED" - "\u2581BETWEEN" - AM - "\u2581HUNDRED" - UM - "\u2581P" - KE - "\u2581REST" - "\u2581GIRL" - "\u2581ALSO" - "\u2581ALMOST" - "\u2581LADY" - "\u2581WHOLE" - "\u2581CO" - "\u2581MO" - "\u2581NOR" - "\u2581FELT" - "\u2581MORNING" - "\u2581AMONG" - "\u2581WAR" - "\u2581YES" - IOUS - "\u2581ASKED" - "\u2581DAYS" - "\u2581FIRE" - "\u2581CALLED" - "\u2581DEAR" - "\u2581SET" - "\u2581HAVING" - "\u2581SINCE" - "\u2581WHOM" - "\u2581PRE" - "\u2581POOR" - "\u2581WORDS" - "\u2581STOOD" - "\u2581OH" - CE - "\u2581HIGH" - "\u2581UNTIL" - "\u2581SMALL" - "\u2581RA" - "\u2581BEST" - "\u2581GAVE" - "\u2581KIND" - "\u2581PERHAPS" - "\u2581COUNTRY" - "\u2581EX" - "\u2581BEGAN" - "\u2581IMP" - "\u2581BOY" - "\u2581ROUND" - "\u2581EM" - "\u2581KING" - "\u2581PRO" - "\u2581HOWEVER" - "\u2581KEEP" - "\u2581SE" - "\u2581W" - "\u2581SP" - TION - "\u2581FACT" - "\u2581TEN" - "\u2581HERSELF" - "\u2581FOUR" - "\u2581NEXT" - "\u2581MYSELF" - "\u2581FIVE" - "\u2581PER" - "\u2581FRIEND" - "\u2581ANYTHING" - "\u2581DI" - "\u2581LOOKING" - "\u2581SAT" - "\u2581POINT" - "\u2581WORD" - "\u2581HOPE" - SON - "\u2581BLACK" - ENCE - "\u2581RATHER" - "\u2581BROUGHT" - "\u2581FULL" - "\u2581LORD" - "\u2581HO" - "\u2581RO" - "\u2581LAND" - TIC - "\u2581HARD" - "\u2581LO" - "\u2581CHILD" - ARY - "\u2581SURE" - "\u2581OPEN" - "\u2581ALONG" - TO - "\u2581AIR" - "\u2581BELIEVE" - "\u2581POWER" - SION - "\u2581VI" - "\u2581TILL" - "\u2581WHOSE" - "\u2581DA" - "\u2581DOES" - URE - "\u2581SEA" - "\u2581DEATH" - "\u2581TAKEN" - "\u2581LAY" - RED - IAL - "\u2581GONE" - "\u2581LI" - "\u2581HEAR" - "\u2581NEAR" - HE - "\u2581PRESENT" - "\u2581CASE" - "\u2581TWENTY" - "\u2581CALL" - "\u2581MATTER" - "\u2581LARGE" - "\u2581FEET" - "\u2581COMP" - "\u2581RED" - "\u2581REASON" - "\u2581OTHERS" - "\u2581SPEAK" - "\u2581WIFE" - OW - "\u2581FORM" - "\u2581TOGETHER" - "\u2581DOCTOR" - ILY - "\u2581PO" - "\u2581NEED" - "\u2581HELP" - "\u2581FEAR" - "\u2581LESS" - "\u2581FA" - "\u2581SON" - "\u2581PASSED" - "\u2581TRUE" - "\u2581INDEED" - "\u2581SOUND" - "\u2581MONEY" - "\u2581SA" - "\u2581CLA" - "\u2581DARK" - "\u2581BEHIND" - "\u2581STRONG" - "\u2581GENERAL" - "\u2581SHORT" - "\u2581SUN" - "\u2581REPLIED" - "\u2581NATURE" - MIN - UN - "\u2581HOUR" - "\u2581CHILDREN" - "\u2581THEMSELVES" - "\u2581ALONE" - UT - "\u2581CANNOT" - "\u2581CARE" - "\u2581NE" - "\u2581ARM" - "\u2581GIVEN" - "\u2581CRIED" - "\u2581READ" - "\u2581ANSWERED" - "\u2581FEEL" - "\u2581MAR" - "\u2581LEAVE" - "\u2581THUS" - MEN - "\u2581STATE" - VING - "\u2581MASTER" - PP - "\u2581THOUSAND" - "\u2581DEAD" - "\u2581CLOSE" - "\u2581DUR" - "\u2581SENT" - "\u2581SIX" - "\u2581ROSE" - "\u2581STA" - "\u2581CAPTAIN" - "\u2581OFTEN" - "\u2581AROUND" - "\u2581BED" - ME - "\u2581TABLE" - "\u2581TURN" - "\u2581SECOND" - "\u2581LU" - BE - "\u2581TOWN" - "\u2581BROTHER" - "\u2581LE" - "\u2581REALLY" - "\u2581PA" - OUR - "\u2581AL" - "\u2581EYE" - "\u2581ORDER" - "\u2581GROUND" - "\u2581COMING" - "\u2581FRIENDS" - "\u2581BIG" - "\u2581WON" - "\u2581DEEP" - "\u2581LEAST" - "\u2581QUESTION" - LEY - "\u2581MET" - "\u2581WOMEN" - "\u2581LIVE" - LES - "\u2581CERTAIN" - "\u2581SHOW" - "\u2581KNOWN" - "\u2581BO" - "\u2581ABOVE" - "\u2581WISH" - "\u2581SOUL" - "\u2581YEAR" - "\u2581MANNER" - "\u2581WITHIN" - "\u2581GA" - "\u2581GRA" - "\u2581HA" - "\u2581USE" - "\u2581SAYS" - "\u2581ALREADY" - "\u2581BAD" - ARD - "\u2581SUDDENLY" - "\u2581HELD" - "\u2581EVENING" - "\u2581SU" - "\u2581SORT" - "\u2581FELL" - "\u2581TIMES" - "\u2581ACT" - "\u2581SC" - "\u2581MEAN" - "\u2581BECOME" - DER - STER - PER - "\u2581ROAD" - "\u2581BAR" - NCE - "\u2581PE" - "\u2581PAST" - "\u2581HORSE" - "\u2581MI" - "\u2581EARTH" - "\u2581STRANGE" - "\u2581CLEAR" - LIE - "\u2581FINE" - "\u2581TALK" - "\u2581RUN" - "\u2581ASK" - "\u2581CA" - ICAL - "\u2581WHETHER" - "\u2581DIDN" - "\u2581USED" - "\u2581LOST" - "\u2581RU" - "\u2581BUSINESS" - "\u2581DOUBT" - "\u2581FE" - "\u2581ANSWER" - "\u2581JOHN" - "\u2581FREE" - RING - "\u2581WIND" - PE - "\u2581RIVER" - "\u2581GU" - "\u2581TRUTH" - "\u2581BEAUTIFUL" - "\u2581SIGHT" - "\u2581LETTER" - "\u2581FAIR" - "\u2581STR" - "\u2581ACROSS" - "\u2581BODY" - "\u2581MAKING" - "\u2581STAND" - 'NO' - VEN - "\u2581SHIP" - "\u2581CHURCH" - "\u2581MU" - "\u2581SENSE" - LAND - END - "\u2581HOLD" - ATING - "\u2581SLEEP" - "\u2581TROUBLE" - "\u2581THOU" - "\u2581TH" - "\u2581ITSELF" - "\u2581PLAY" - "\u2581BRING" - "\u2581ARMS" - "\u2581KEPT" - "\u2581ENGLISH" - RIC - "\u2581CONS" - "\u2581SCHOOL" - "\u2581GLAD" - "\u2581EVERYTHING" - "\u2581HUMAN" - "\u2581STORY" - "\u2581LOW" - "\u2581CHA" - "\u2581LAW" - "\u2581LINE" - "\u2581RETURNED" - "\u2581EITHER" - "\u2581RETURN" - LIC - ATIONS - ACH - "\u2581CITY" - BER - "\u2581BOAT" - "\u2581MEANS" - GED - "\u2581FAMILY" - "\u2581SEVERAL" - "\u2581ILL" - "\u2581LATE" - "\u2581COLD" - "\u2581RAN" - "\u2581TOWARDS" - "\u2581BA" - WARD - "\u2581INTEREST" - "\u2581FO" - "\u2581PERSON" - "\u2581HAIR" - "\u2581PLAN" - "\u2581FOOT" - "\u2581READY" - "\u2581BECAME" - "\u2581SUBJECT" - "\u2581SPOKE" - "\u2581BOOK" - BY - "\u2581CRE" - QU - "\u2581FELLOW" - PED - "\u2581ABLE" - "\u2581SUPPOSE" - "\u2581POSSIBLE" - ADE - "\u2581HI" - "\u2581PAIN" - "\u2581WILD" - "\u2581BLOOD" - "\u2581HU" - "\u2581FOLLOWED" - "\u2581CHANCE" - "\u2581REMEMBER" - "\u2581EIGHTEEN" - "\u2581NUMBER" - TEN - "\u2581JU" - "\u2581AB" - "\u2581UNDERSTAND" - LIN - "\u2581ART" - "\u2581CUT" - "\u2581SPIRIT" - "\u2581YE" - "\u2581DREAM" - "\u2581ELSE" - "\u2581SWEET" - "\u2581HAR" - "\u2581SEEM" - QUE - PLE - "\u2581SH" - DEN - "\u2581THY" - "\u2581HUSBAND" - "\u2581EFFECT" - "\u2581BREATH" - "\u2581AGE" - PING - "\u2581RESPECT" - "\u2581PASS" - "\u2581SOMETIMES" - "\u2581STAY" - "\u2581REAL" - "\u2581FORWARD" - "\u2581THEREFORE" - "\u2581PI" - "\u2581CHARACTER" - NED - COM - THE - NER - DO - "\u2581BU" - "\u2581SISTER" - ELL - "\u2581DAUGHTER" - "\u2581SIGN" - "\u2581TOWARD" - "\u2581VISIT" - "\u2581JA" - "\u2581PAY" - RIS - TRI - "\u2581PRETTY" - "\u2581SAINT" - "\u2581COMMON" - "\u2581REACHED" - "\u2581IDEA" - "\u2581REC" - "\u2581HAPPY" - "\u2581VIEW" - "\u2581BOYS" - "\u2581MINE" - GRA - "\u2581DIFFERENT" - "\u2581COURT" - ILL - "\u2581FEELING" - "\u2581CUR" - CO - "\u2581LATER" - "\u2581REMAIN" - "\u2581SHA" - "\u2581BRIGHT" - "\u2581WINDOW" - "\u2581STREET" - "\u2581WA" - "\u2581TAKING" - "\u2581HOURS" - "\u2581SMILE" - "\u2581FRONT" - "\u2581BEAR" - "\u2581HAT" - "\u2581JO" - GO - UGH - "\u2581EIGHT" - "\u2581SUB" - "\u2581SEVEN" - "\u2581CAUSE" - "\u2581FORCE" - "\u2581FALL" - "\u2581OUGHT" - "\u2581CHIEF" - "\u2581BIT" - "\u2581CHANGE" - "\u2581DEAL" - "\u2581GREEN" - "\u2581HEAVEN" - "\u2581RICH" - LER - "\u2581CONTINUED" - ISM - "\u2581BLUE" - "\u2581DES" - "\u2581PARTY" - "\u2581LONGER" - "\u2581SEEMS" - "\u2581APPEARED" - "\u2581TRE" - CTION - "\u2581STONE" - "\u2581CHAIR" - "\u2581JE" - "\u2581PUBLIC" - "\u2581CAP" - "\u2581WANTED" - IF - ABLY - "\u2581TU" - "\u2581DOING" - "\u2581PEN" - "\u2581ADDED" - "\u2581COUNT" - "\u2581FAST" - "\u2581FIGURE" - "\u2581BEYOND" - "\u2581MEET" - "\u2581STE" - "\u2581ACCOUNT" - CU - "\u2581GI" - "\u2581COR" - "\u2581AGO" - MON - "\u2581JOY" - "\u2581DU" - "\u2581FRENCH" - ITIES - "\u2581TOP" - "\u2581GLANCE" - "\u2581FOLLOW" - "\u2581OPENED" - "\u2581LED" - "\u2581TRANS" - SHIP - "\u2581OBJECT" - IBLE - "\u2581SEND" - FOR - "\u2581VER" - "\u2581SILENCE" - ILE - RIE - "\u2581SI" - "\u2581SECRET" - "\u2581TONE" - "\u2581B" - "\u2581H" - "\u2581HALL" - "\u2581EARLY" - "\u2581CERTAINLY" - "\u2581COMMAND" - "\u2581EL" - GER - "\u2581PURPOSE" - "\u2581COMPANY" - "\u2581POSITION" - "\u2581TRAIN" - AIN - "\u2581FI" - "\u2581TRIED" - "\u2581CARRIED" - "\u2581THANK" - UC - BU - "\u2581NONE" - "\u2581SERVICE" - "\u2581WI" - "\u2581SAYING" - "\u2581JACK" - KING - "\u2581LIPS" - "\u2581TRY" - "\u2581RECEIVED" - "\u2581GARDEN" - "\u2581GOLD" - "\u2581ALTHOUGH" - "\u2581MINUTES" - "\u2581EXCEPT" - "\u2581ENTERED" - "\u2581WAIT" - "\u2581SELF" - "\u2581MOR" - "\u2581CAMP" - "\u2581WALL" - "\u2581ENGLAND" - "\u2581WALK" - "\u2581FURTHER" - "\u2581LIVING" - "\u2581NEARLY" - "\u2581COMES" - "\u2581MILES" - "\u2581SCENE" - "\u2581PICTURE" - "\u2581DRESS" - "\u2581PLEASURE" - ENED - "\u2581WATCH" - "\u2581SLOWLY" - "\u2581TREES" - CON - "\u2581NEITHER" - ITION - "\u2581APP" - "\u2581YOURSELF" - HER - "\u2581KA" - "\u2581FORTH" - MBLE - "\u2581GRAVE" - "\u2581WARM" - RIES - "\u2581WALKED" - "\u2581OCCASION" - "\u2581GENTLEMAN" - "\u2581THIRTY" - "\u2581WONDER" - "\u2581SILENT" - "\u2581GIRLS" - "\u2581DIE" - "\u2581FIT" - "\u2581UNCLE" - VAL - "\u2581BANK" - "\u2581WOOD" - "\u2581LEARN" - "\u2581FIFTY" - "\u2581MOUTH" - "\u2581STANDING" - "\u2581DREW" - GLE - "\u2581BELL" - "\u2581PH" - "\u2581WIDE" - "\u2581CROWD" - "\u2581THINKING" - "\u2581START" - "\u2581POST" - "\u2581PAN" - "\u2581TRI" - "\u2581OFFICE" - "\u2581CAUGHT" - "\u2581EXPERIENCE" - QUI - "\u2581ATTENTION" - RESS - WAY - "\u2581EAT" - "\u2581GRAND" - "\u2581APPEAR" - "\u2581DISTANCE" - "\u2581QUIET" - "\u2581NORTH" - "\u2581VA" - "\u2581COMPANION" - HAM - "\u2581SAVE" - "\u2581AFRAID" - "\u2581DESIRE" - "\u2581CROSS" - ECT - "\u2581PRINCE" - OU - "\u2581PORT" - "\u2581HEAVY" - "\u2581ATTEMPT" - "\u2581PLAIN" - "\u2581SAL" - "\u2581HAPPENED" - "\u2581BOUND" - "\u2581EXPECT" - "\u2581MAD" - "\u2581TREE" - "\u2581LAID" - "\u2581REACH" - "\u2581NECESSARY" - "\u2581BI" - "\u2581SPRING" - "\u2581SAFE" - "\u2581WEEK" - "\u2581WRONG" - "\u2581CONDITION" - CRI - MENTS - "\u2581STARTED" - "\u2581MUSIC" - "\u2581TRUST" - "\u2581SOUTH" - MIS - "\u2581LIVED" - "\u2581DOG" - UP - "\u2581LENGTH" - "\u2581FOLLOWING" - "\u2581SIT" - LET - "\u2581J" - "\u2581MARY" - "\u2581STEP" - CHE - ORY - KIN - "\u2581STAR" - "\u2581STOPPED" - "\u2581PAPER" - "\u2581DINNER" - "\u2581GETTING" - CENT - "\u2581FISH" - "\u2581DAM" - "\u2581EXCLAIMED" - "\u2581BOW" - "\u2581BEAUTY" - "\u2581BLOW" - "\u2581ROCK" - "\u2581BRA" - "\u2581YOUTH" - AND - "\u2581OB" - RON - "\u2581STRAIGHT" - "\u2581FRANK" - "\u2581NATURAL" - AIL - "\u2581BOARD" - "\u2581LAUGHED" - VOL - "\u2581TOUCH" - "\u2581HARDLY" - PAR - "\u2581AMERICAN" - "\u2581WEST" - "\u2581CORNER" - "\u2581CHE" - NG - "\u2581AUNT" - "\u2581STU" - "\u2581BORN" - "\u2581CRA" - "\u2581KNOWLEDGE" - "\u2581SIN" - "\u2581OPINION" - "\u2581PEACE" - "\u2581BROKEN" - "\u2581BROWN" - "\u2581VILLAGE" - "\u2581TEA" - "\u2581HILL" - "\u2581DIRECTION" - "\u2581INSTEAD" - "\u2581LONDON" - "\u2581PLEASE" - "\u2581FRESH" - "\u2581FLOOR" - "\u2581EXPRESSION" - IFIED - "\u2581RESULT" - "\u2581TW" - "\u2581QUICKLY" - "\u2581WAITING" - "\u2581PROBABLY" - "\u2581WHATEVER" - "\u2581SHADOW" - "\u2581STRUCK" - "\u2581FORGET" - "\u2581LOVED" - "\u2581MARCH" - "\u2581GOVERNMENT" - "\u2581THOUGHTS" - DIC - "\u2581BESIDE" - "\u2581KNOWS" - "\u2581CHARGE" - "\u2581ISLAND" - "\u2581NOBLE" - "\u2581QUICK" - "\u2581PAR" - "\u2581HORSES" - SIDE - "\u2581DEN" - "\u2581WEAR" - "\u2581SHOT" - "\u2581PU" - "\u2581EFFORT" - GUE - "\u2581REMAINED" - "\u2581REGARD" - FULLY - USE - "\u2581SAD" - "\u2581FIGHT" - "\u2581WRITE" - "\u2581SPOT" - "\u2581SEEING" - CING - "\u2581DANGER" - "\u2581CAST" - "\u2581JUDGE" - "\u2581STRENGTH" - "\u2581SITTING" - "\u2581DUTY" - TUR - "\u2581MARK" - "\u2581AFTERNOON" - ULT - "\u2581REP" - "\u2581GUARD" - "\u2581MIN" - "\u2581BILL" - "\u2581TEARS" - "\u2581MAKES" - "\u2581DIED" - ESS - "\u2581NINE" - "\u2581FORTY" - "\u2581COL" - "\u2581GREW" - "\u2581EASY" - ZZ - "\u2581BRI" - "\u2581FILLED" - "\u2581MOVED" - ALLY - CHES - "\u2581SLA" - "\u2581BELOW" - "\u2581SNOW" - "\u2581OUTSIDE" - "\u2581BATTLE" - "\u2581PLACED" - "\u2581CHRIS

Keywords

python, speech-synthesis, pytorch, machine-translation, ESPnet, speech-translation, deep-learning, speech-recognition

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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