ESPnet pretrained model, Shinji Watanabe/asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best, fs=16000, lang=en
Creators: name: Watanabe, Shinji
Publisher: name: Zenodo
Year: 2020
Subjects: ESPnet
deep-learning
python
pytorch
speech-recognition
speech-synthesis
speech-translation
machine-translation

description: This model was trained by Shinji Watanabe using librispeech/asr1 recipe in espnet. <strong>Python API</strong> <pre><code class="language-python">See https://github.com/espnet/espnet_model_zoo</code></pre> <strong>Evaluate in the recipe</strong> <pre><code class="language-bash">git clone https://github.com/espnet/espnet cd espnet git checkout fca1edc18f8235c1de13925147519e6ecd03ec96 pip install -e . cd asr1/downloads/9799876d5af386693377185b6fd68a2b ./run.sh --skip_data_prep false --skip_train true --download_model </code> </pre> <strong>Results</strong> <pre><code># RESULTS ## Environments - date: `Tue Jul 21 07:58:39 EDT 2020` - python version: `3.7.3 (default, Mar 27 2019, 22:11:17) [GCC 7.3.0]` - espnet version: `espnet 0.8.0` - pytorch version: `pytorch 1.4.0` - Git hash: `75db853dd26a40d3d4dd979b2ff2457fbbb0cd69` - Commit date: `Mon Jul 20 10:49:12 2020 -0400` ## asr_train_asr_transformer_e18_raw_bpe_sp ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_dev_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|54402|97.9|1.8|0.2|0.2|2.3|28.2| |decode_dev_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|54402|97.9|1.9|0.2|0.3|2.4|29.5| |decode_dev_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|50948|94.6|4.7|0.7|0.7|6.0|46.6| |decode_dev_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|50948|94.4|5.0|0.5|0.8|6.3|47.5| |decode_test_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|52576|97.7|2.0|0.3|0.3|2.6|30.4| |decode_test_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|52576|97.7|2.0|0.2|0.3|2.6|30.1| |decode_test_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|52343|94.5|4.8|0.7|0.7|6.2|49.7| |decode_test_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|52343|94.3|5.1|0.6|0.8|6.5|50.3| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_dev_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|288456|99.3|0.3|0.3|0.2|0.9|28.2| |decode_dev_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|288456|99.3|0.4|0.3|0.2|0.9|29.5| |decode_dev_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|265951|97.7|1.2|1.1|0.6|2.9|46.6| |decode_dev_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|265951|97.7|1.3|1.0|0.8|3.0|47.5| |decode_test_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|281530|99.3|0.3|0.4|0.3|1.0|30.4| |decode_test_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|281530|99.4|0.3|0.3|0.3|0.9|30.1| |decode_test_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|272758|97.8|1.1|1.1|0.7|2.9|49.7| |decode_test_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|272758|97.9|1.2|0.9|0.8|2.9|50.3| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_dev_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|69307|97.2|1.8|1.0|0.4|3.2|28.2| |decode_dev_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2703|69307|97.2|1.9|1.0|0.5|3.3|29.5| |decode_dev_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|64239|93.3|4.4|2.2|1.2|7.9|46.6| |decode_dev_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2864|64239|93.2|4.9|1.9|1.5|8.3|47.5| |decode_test_clean_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|66712|97.0|1.9|1.1|0.4|3.3|30.4| |decode_test_clean_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2620|66712|97.1|1.9|1.0|0.5|3.3|30.1| |decode_test_other_decode_asr_beam_size20_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|66329|93.1|4.5|2.4|1.0|7.9|49.7| |decode_test_other_decode_asr_beam_size5_lm_train_lm_adam_bpe_valid.loss.best_asr_model_valid.acc.best|2939|66329|93.1|4.8|2.1|1.4|8.3|50.3|</code></pre> <strong>ASR config</strong> <pre><code>accum_grad: 6 allow_variable_data_keys: false batch_bins: 15000000 batch_size: 20 batch_type: numel best_model_criterion: - - valid - acc - max bpemodel: data/token_list/bpe_unigram5000/bpe.model chunk_length: 500 chunk_shift_ratio: 0.5 cleaner: null collect_stats: false config: conf/tuning/train_asr_transformer_e18.yaml ctc_conf: ctc_type: builtin dropout_rate: 0.0 reduce: true cudnn_benchmark: false cudnn_deterministic: true cudnn_enabled: true decoder: transformer decoder_conf: attention_heads: 8 dropout_rate: 0.1 linear_units: 2048 num_blocks: 6 positional_dropout_rate: 0.1 self_attention_dropout_rate: 0.1 src_attention_dropout_rate: 0.1 dist_backend: nccl dist_init_method: env:// dist_launcher: null dist_master_addr: localhost dist_master_port: 33643 dist_rank: 3 dist_world_size: 4 distributed: true dry_run: false early_stopping_criterion: - valid - loss - min encoder: transformer encoder_conf: attention_dropout_rate: 0.1 attention_heads: 8 dropout_rate: 0.1 input_layer: conv2d6 linear_units: 2048 normalize_before: true num_blocks: 18 output_size: 512 positional_dropout_rate: 0.1 fold_length: - 80000 - 150 frontend: default frontend_conf: fs: 16k g2p: null grad_clip: 5.0 grad_noise: false init: xavier_uniform input_size: null iterator_type: sequence keep_nbest_models: 10 local_rank: 3 log_interval: null log_level: INFO max_cache_size: 0.0 max_epoch: 100 model_conf: ctc_weight: 0.3 length_normalized_loss: false lsm_weight: 0.1 multiple_iterator: false multiprocessing_distributed: true ngpu: 1 no_forward_run: false non_linguistic_symbols: null normalize: global_mvn normalize_conf: stats_file: exp/asr_stats_raw_sp/train/feats_stats.npz num_att_plot: 3 num_cache_chunks: 1024 num_iters_per_epoch: null num_workers: 1 optim: adam optim_conf: lr: 0.002 output_dir: exp/asr_train_asr_transformer_e18_raw_bpe_sp patience: null pretrain_key: [] pretrain_path: [] print_config: false required: - output_dir - token_list resume: true scheduler: warmuplr scheduler_conf: warmup_steps: 25000 seed: 0 sort_batch: descending sort_in_batch: descending specaug: specaug specaug_conf: apply_freq_mask: true apply_time_mask: true apply_time_warp: true freq_mask_width_range: - 0 - 30 num_freq_mask: 2 num_time_mask: 2 time_mask_width_range: - 0 - 40 time_warp_mode: bicubic time_warp_window: 5 token_list: - - - "\u2581EXCLAIM" - "\u2581OPPORTUNITIES" - "\u2581REMEDY" - "\u2581DEFENSE" - "\u2581ETERNITY" - "\u2581SKULL" - "\u2581PLEADED" - "\u2581INSTINCTIVELY" - "\u2581SLAUGHTER" - "\u2581RATIONAL" - "\u2581PULSE" - "\u2581PARALLEL" - "\u2581SCOUNDREL" - "\u2581PRUDENCE" - "\u2581PROBABILITY" - "\u2581DERIVED" - "\u2581MONSTROUS" - "\u2581POTATOES" - "\u2581IMPRESSIVE" - "\u2581DAINTY" - "\u2581SULTAN" - "\u2581CARPENTER" - "\u2581INNUMERABLE" - "\u2581INVITE" - "\u2581CIRCULAT" - "\u2581ELOQUENCE" - "\u2581DISCIPLE" - "\u2581ATTIRE" - "\u2581OBSTINATE" - "\u2581STREAK" - "\u2581WOLVES" - "\u2581GRINNED" - "\u2581ORCHARD" - "\u2581JAPANESE" - "\u2581ANNUAL" - "\u2581SHAWL" - "\u2581PACIFIC" - "\u2581VEHICLE" - "\u2581APOSTLE" - "\u2581CONGREGATION" - "\u2581AMAZING" - "\u2581OCCURRENCE" - "\u2581CONFERENCE" - "\u2581MIXTURE" - "\u2581EXAMINING" - "\u2581SAUCE" - "\u2581ADMIRING" - "\u2581AMBASSADOR" - "\u2581DEVICE" - "\u2581INCAPABLE" - "\u2581WHEREUPON" - "\u2581IMPERFECT" - "\u2581PERCEPTION" - "\u2581LOUNG" - "\u2581VACANT" - "\u2581EXCURSION" - "\u2581DISCOURAGE" - "\u2581FANTASTIC" - "\u2581REBELLION" - "\u2581CONVINCE" - "\u2581DEFIANCE" - "\u2581CONNECT" - "\u2581EMPHASIS" - "\u2581MEXICO" - "\u2581OPPONENT" - "\u2581DETERMINE" - "\u2581MANUSCRIPT" - "\u2581INCESSANT" - "\u2581BRONZE" - "\u2581COURTEOUS" - "\u2581COFFIN" - "\u2581CONSTRUCTION" - "\u2581BLUNDER" - "\u2581SENATE" - "\u2581CIRCUM" - "\u2581DANIEL" - "\u2581ELOQUENT" - "\u2581QUIVERING" - "\u2581VIGIL" - "\u2581HAZARD" - "\u2581UNWORTHY" - "\u2581TAB" - "\u2581ILLUSION" - "\u2581AGITATED" - "\u2581CHAMPION" - "\u2581DIMINISH" - "\u2581STUMP" - "\u2581CONFIDE" - "\u2581PHILADELPHIA" - "\u2581DOUGLAS" - "\u2581BUMP" - "\u2581COMMERCE" - "\u2581FACULTY" - "\u2581CONFEDERATE" - "\u2581EMBARRASSMENT" - "\u2581EXPLORE" - "\u2581MAGGIE" - "\u2581PHILOSOPHIC" - "\u2581ADMINISTRATION" - "\u2581HEADQUARTERS" - "\u2581SOLUTION" - "\u2581REFRAIN" - "\u2581ELDEST" - "\u2581FORMIDABLE" - "\u2581VERANDA" - "\u2581DISMAL" - "\u2581ESTHER" - "\u2581PRUDENT" - "\u2581BLAZING" - "\u2581RESOLVE" - "\u2581ELSIE" - "\u2581TURKEY" - "\u2581DECREE" - "\u2581CONVERSE" - "\u2581GRAVITY" - "\u2581MIRTH" - "\u2581RESEMBLANCE" - "\u2581GULF" - "\u2581SHRUB" - "\u2581EXHIBITION" - "\u2581AUSTRALIA" - "\u2581ELEANOR" - "\u2581UNCOMMON" - "\u2581RACHEL" - "\u2581TOMORROW" - "\u2581INJUSTICE" - "\u2581WISTFUL" - "\u2581WREATH" - "\u2581DISDAIN" - "\u2581CRUMB" - "\u2581CLINGING" - "\u2581COMMEND" - "\u2581SUPERSTITION" - "\u2581CRISIS" - "\u2581MAXIM" - "\u2581DESIRABLE" - "\u2581GIGANTIC" - "\u2581JUNGLE" - "\u2581DIGNIFIED" - "\u2581INVALID" - "\u2581UNNECESSARY" - "\u2581SUBLIME" - "\u2581PLOUGH" - "\u2581SUFFICE" - "\u2581BUNK" - "\u2581LUNCHEON" - "\u2581DRAUGHT" - "\u2581COLONY" - "\u2581PARLOUR" - "\u2581TERRIFIED" - "\u2581LOATH" - "\u2581SIGNIFICANCE" - "\u2581EXTENSIVE" - "\u2581HORACE" - "\u2581SERENE" - "\u2581CHEESE" - "\u2581PRECEDING" - "\u2581LEVI" - "\u2581INVARIABLY" - "\u2581OBSERVING" - "\u2581EARLIEST" - "\u2581WHEAT" - "\u2581DEMOCRAT" - "\u2581YOURSELVES" - "\u2581FEMININE" - "\u2581ARTIFICIAL" - "\u2581IDIOT" - "\u2581TORRENT" - "\u2581CONVICT" - "\u2581CONSUME" - "\u2581EMBROIDER" - "\u2581CONQUEST" - "\u2581CALCULATED" - "\u2581HAPPIER" - "\u2581DECAY" - "\u2581LITERALLY" - "\u2581RADIANT" - ENNI - "\u2581AMAZED" - "\u2581SPLIT" - "\u2581SUPPOSING" - "\u2581CANADA" - "\u2581PAVEMENT" - "\u2581ANTHONY" - "\u2581BULK" - "\u2581MEDIUM" - "\u2581MAURICE" - "\u2581SALOON" - "\u2581BARRIER" - "\u2581SWORE" - GUARD - "\u2581TEMPORARY" - "\u2581STALK" - "\u2581IRREGULAR" - "\u2581FRANTIC" - "\u2581BLISS" - "\u2581CONSPICUOUS" - "\u2581GERALD" - "\u2581EXCITING" - "\u2581SMASH" - "\u2581EXTERNAL" - "\u2581HESITATE" - "\u2581PATHETIC" - "\u2581NINTH" - "\u2581HAMILTON" - "\u2581UNSEEN" - "\u2581DEFECT" - "\u2581ACCURATE" - "\u2581LIQUOR" - "\u2581ENLIGHTEN" - WICH - "\u2581CLARK" - "\u2581REVERSE" - "\u2581PRIMITIVE" - "\u2581BLUFF" - "\u2581PRECAUTION" - "\u2581AWHILE" - "\u2581SPOON" - "\u2581TEMPERAMENT" - "\u2581SCHOONER" - "\u2581FREDERICK" - "\u2581REMORSE" - "\u2581CUSHION" - "\u2581EXCLUSIVE" - "\u2581CONTEMPLATE" - "\u2581SYLVIA" - "\u2581SITUATED" - "\u2581SKIPPER" - "\u2581DESOLATE" - "\u2581WORRIED" - "\u2581DWELT" - "\u2581TROUSERS" - "\u2581MARTYR" - "\u2581RIV" - "\u2581MEXICAN" - "\u2581DIVIDE" - "\u2581AMIABLE" - "\u2581PRUSSIA" - "\u2581COMMERCIAL" - "\u2581CONFRONT" - MPTON - "\u2581PROSPERITY" - "\u2581FEBRUARY" - "\u2581ADJUST" - "\u2581FUGITIVE" - "\u2581ABUNDANT" - "\u2581CRUELTY" - "\u2581UNCOMFORTABLE" - "\u2581THUMB" - "\u2581LAWRENCE" - "\u2581INTERCOURSE" - "\u2581STUDIO" - "\u2581PROMINENT" - "\u2581CHARLOTTE" - SHAW - "\u2581BRETHREN" - "\u2581COMPLEXION" - "\u2581TRAITOR" - "\u2581UNJUST" - BOAT - "\u2581TICK" - "\u2581KNELT" - "\u2581PROPRIETOR" - "\u2581ELABORATE" - "\u2581WRIT" - "\u2581OBSTACLE" - "\u2581CONSOLATION" - "\u2581DETAIN" - "\u2581FLANK" - "\u2581SAXON" - "\u2581SCRIPTURE" - "\u2581PERFUME" - "\u2581TRAGIC" - "\u2581EGYPTIAN" - "\u2581FOWL" - Q - "\u2581NOWHERE" - ARIA - "\u2581ATTENTIVE" - "\u2581STAIRCASE" - "\u2581BRITAIN" - "\u2581NORMAL" - "\u2581INFLICT" - "\u2581ECONOMI" - "\u2581OXFORD" - OTTE - "\u2581TUMULT" - "\u2581CLIMATE" - "\u2581CONTRIBUTE" - "\u2581TEMPEST" - "\u2581DISASTER" - "\u2581HYMN" - "\u2581FIERY" - "\u2581SUPERINTEND" - "\u2581SHERIFF" - "\u2581REVOLT" - "\u2581SURPRISING" - "\u2581DOWNSTAIRS" - "\u2581STRAY" - "\u2581QUAINT" - "\u2581SHAKESPEARE" - "\u2581WITHDREW" - "\u2581INJURY" - "\u2581SUPPLIES" - "\u2581PUMP" - "\u2581COMPASSION" - "\u2581DEVOUR" - "\u2581TENDENCY" - "\u2581VEGETABLE" - "\u2581BEHALF" - "\u2581SCOTCH" - "\u2581ALFRED" - "\u2581SPHERE" - "\u2581BACKGROUND" - "\u2581BEWILDERED" - "\u2581CONCLUD" - "\u2581COMPOSITION" - "\u2581EXTRACT" - "\u2581DIPLOMA" - "\u2581INQUIRIES" - "\u2581DESTINED" - "\u2581CONFOUND" - "\u2581INHABIT" - "\u2581DISTRACT" - "\u2581PILLAR" - "\u2581TELEGRAM" - "\u2581HENRI" - "\u2581HARBOUR" - "\u2581BONNET" - "\u2581COMBINATION" - "\u2581PLEASING" - "\u2581CABINET" - "\u2581SWAMP" - "\u2581SYN" - "\u2581HARVEST" - "\u2581RIGHTEOUS" - "\u2581TRUMPET" - "\u2581ARTILLERY" - "\u2581RIGID" - "\u2581EDITH" - "\u2581RELUCTANT" - "\u2581COURTESY" - "\u2581CEILING" - "\u2581ATTRACTION" - "\u2581ASSAULT" - "\u2581CHICAGO" - "\u2581GLIDE" - "\u2581EXCEED" - "\u2581CONCERT" - "\u2581ORGANIZATION" - "\u2581INVENTION" - "\u2581RASCAL" - "\u2581PATTERN" - "\u2581RESOLUTE" - "\u2581INVESTIGATION" - ABOUT - "\u2581LUXURY" - "\u2581YACHT" - "\u2581SHRINK" - "\u2581ARDENT" - "\u2581RESORT" - "\u2581MUSKET" - "\u2581INCLINATION" - "\u2581ALEXANDER" - "\u2581SWARM" - "\u2581TRAVERS" - "\u2581CLARA" - "\u2581TESTIMONY" - "\u2581AGITATION" - "\u2581RECOGNITION" - "\u2581BELIEVING" - "\u2581AFFIRM" - "\u2581FRONTIER" - "\u2581TERRITORY" - "\u2581PARLOR" - "\u2581GRIEVE" - "\u2581REMEMBRANCE" - "\u2581SATISFACTORY" - "\u2581SIGNIFICANT" - "\u2581THRESHOLD" - "\u2581CATHEDRAL" - "\u2581HISTORICAL" - "\u2581MONUMENT" - "\u2581FORTNIGHT" - "\u2581ANCESTOR" - "\u2581SENATOR" - "\u2581LIMP" - "\u2581FROZEN" - "\u2581INNOCENCE" - "\u2581ADAPT" - "\u2581ENVY" - "\u2581SALVATION" - "\u2581CRYSTAL" - "\u2581SYMPATHETIC" - "\u2581TACT" - "\u2581CARDINAL" - "\u2581PROFESS" - "\u2581ADVERTISE" - "\u2581HORRID" - "\u2581EXERTION" - "\u2581CROOK" - "\u2581TERRIBLY" - "\u2581CALIFORNIA" - "\u2581IMPATIENCE" - "\u2581ISRAEL" - "\u2581WORM" - "\u2581DESTINY" - "\u2581EXAGGERAT" - "\u2581MOIST" - "\u2581SPLASH" - "\u2581MARVELLOUS" - "\u2581DISCOURSE" - "\u2581ENTITLED" - "\u2581LAUNCH" - "\u2581PUNCH" - "\u2581KITTY" - "\u2581RELAX" - "\u2581DROOP" - "\u2581FLOURISH" - "\u2581STRICKEN" - "\u2581ERRAND" - "\u2581CONVENT" - "\u2581JOHNNY" - "\u2581SHAFT" - "\u2581SLIM" - "\u2581PRAIRIE" - "\u2581INDEPENDENCE" - "\u2581TIGER" - LOP - "\u2581DEAF" - "\u2581EDUCATED" - "\u2581OBLIGATION" - "\u2581NECESSARILY" - "\u2581CASUAL" - "\u2581EMINENT" - "\u2581WARRANT" - RVA - "\u2581ADMIRABLE" - "\u2581FEATURE" - "\u2581VOLUNTEER" - "\u2581PLEDGE" - "\u2581MAGISTRATE" - "\u2581INSPIRATION" - "\u2581WRIST" - "\u2581SULLEN" - "\u2581MANUFACTURE" - "\u2581MONDAY" - "\u2581CERTAINTY" - "\u2581CELLAR" - "\u2581SERPENT" - "\u2581MONKEY" - "\u2581APPROPRIATE" - "\u2581PENCIL" - "\u2581ESSAY" - "\u2581ULTIMATE" - "\u2581HEROIC" - "\u2581DISCERN" - "\u2581MEDICAL" - "\u2581TOMMY" - "\u2581STUDIES" - "\u2581GORDON" - "\u2581DECEMBER" - "\u2581PARADISE" - BOROUGH - "\u2581OBEDIENCE" - "\u2581JACKET" - "\u2581GARRISON" - "\u2581GUILT" - "\u2581SUCCESSION" - "\u2581CONSTRUCT" - "\u2581PENETRATE" - "\u2581ANGRILY" - "\u2581TRANQUIL" - "\u2581CONSTITUTE" - "\u2581NANCY" - "\u2581ACCESS" - "\u2581ESTIMATE" - "\u2581TICKET" - "\u2581ADVANCING" - "\u2581BRUTAL" - "\u2581CORRUPT" - "\u2581COPPER" - "\u2581WHIM" - "\u2581BROOD" - "\u2581PERSECUT" - "\u2581JERRY" - "\u2581INFERIOR" - "\u2581PRODUCTION" - FEL - "\u2581SCANDAL" - "\u2581SMOT" - "\u2581APPOINTMENT" - "\u2581PROPOSAL" - "\u2581REVERENCE" - "\u2581HOARSE" - "\u2581SHREWD" - "\u2581SPECTATOR" - "\u2581SNEER" - "\u2581TERRACE" - "\u2581SECURITY" - "\u2581NEIGHBORHOOD" - "\u2581OUTRAGE" - "\u2581UNWILLING" - "\u2581CRAZY" - "\u2581COMPARISON" - "\u2581STRENGTHEN" - "\u2581PRESUME" - "\u2581ADORN" - "\u2581REJOINED" - "\u2581CHERISH" - "\u2581IMPORT" - "\u2581DISORDER" - MOUTH - "\u2581ELEGANT" - "\u2581HARMONY" - "\u2581SURGEON" - "\u2581DESPATCH" - "\u2581INDUSTRY" - "\u2581UNEASY" - "\u2581OVERLOOK" - "\u2581PIERRE" - "\u2581PRODUCT" - "\u2581THIEF" - "\u2581RECOGNISED" - "\u2581PIERCE" - FOOT - "\u2581AMUSING" - "\u2581SUBSEQUENT" - "\u2581APPLICATION" - "\u2581TREAD" - "\u2581EDITION" - "\u2581STRUCTURE" - "\u2581LANDLORD" - "\u2581BRISK" - "\u2581NAUGHT" - "\u2581SHRILL" - "\u2581CORRIDOR" - "\u2581DRAMATIC" - "\u2581ABSTRACT" - "\u2581SENOR" - "\u2581WRETCH" - "\u2581CONVENIENT" - OLU - "\u2581DISMAY" - "\u2581CONTEST" - "\u2581IDOL" - "\u2581ASSEMBLY" - "\u2581CLUNG" - "\u2581IGNOR" - "\u2581FRIGHTFUL" - "\u2581INQUIRE" - "\u2581CULTURE" - "\u2581LEGEND" - "\u2581DROPPING" - "\u2581ANGUISH" - "\u2581ESTABLISH" - "\u2581ENSU" - "\u2581PIRATE" - "\u2581GLANCING" - "\u2581AVERAGE" - "\u2581MEMORIES" - "\u2581NIECE" - "\u2581SLUMBER" - ETTA - "\u2581ELECTION" - "\u2581OBSCURE" - "\u2581UNDOUBTEDLY" - "\u2581PONY" - "\u2581PILOT" - "\u2581SARAH" - "\u2581RIBBON" - "\u2581IMPROVEMENT" - "\u2581PRECEDE" - "\u2581APPREHENSION" - "\u2581INEVITABLE" - "\u2581PRACTISE" - "\u2581ABUSE" - LIUS - "\u2581GOSSIP" - "\u2581DIFFER" - "\u2581CHATTER" - "\u2581INVISIBLE" - "\u2581CHORUS" - "\u2581PERMANENT" - "\u2581JANUARY" - "\u2581PROCLAIM" - "\u2581AUTHORITIES" - "\u2581CHALLENGE" - COTT - "\u2581SALUTE" - "\u2581POMP" - "\u2581SUPPLIED" - "\u2581THITHER" - "\u2581RETORTED" - DOLPH - "\u2581BARBARA" - "\u2581ATTRACTIVE" - GUI - "\u2581EXCLAMATION" - "\u2581OCCUPY" - "\u2581ELLEN" - "\u2581LANDSCAPE" - "\u2581CHANGING" - "\u2581BUFFALO" - "\u2581GALLERY" - "\u2581CLOSING" - "\u2581SOFTEN" - "\u2581CHINESE" - "\u2581NIGH" - "\u2581NAR" - "\u2581FLOATING" - "\u2581AUSTRIA" - "\u2581CHICKEN" - "\u2581CAUTION" - "\u2581CRITICISM" - "\u2581VENGEANCE" - "\u2581IMPERIAL" - "\u2581NOVEMBER" - "\u2581DOCUMENT" - "\u2581ARCHITECT" - "\u2581IMPART" - "\u2581RESPONSE" - "\u2581CONTRADICT" - "\u2581QUOTE" - "\u2581SIMPLICITY" - "\u2581AROUSED" - "\u2581BOMB" - TTIE - "\u2581TELEGRAPH" - "\u2581PILGRIM" - "\u2581MAGAZINE" - WYN - "\u2581RECKLESS" - "\u2581SCRATCH" - "\u2581CASH" - "\u2581RESISTANCE" - "\u2581MUTUAL" - "\u2581ATTRIBUTE" - "\u2581STOMACH" - "\u2581FUNCTION" - "\u2581SENSITIVE" - BOY - "\u2581SCREEN" - "\u2581PROPOSITION" - "\u2581PICTURESQUE" - "\u2581DELICIOUS" - "\u2581HESITATION" - "\u2581GLEN" - "\u2581REVIEW" - "\u2581SUMMIT" - "\u2581INTELLECT" - "\u2581GREETED" - "\u2581BLADE" - "\u2581SOFA" - "\u2581SUNLIGHT" - "\u2581HAPPILY" - "\u2581CULTIVATE" - "\u2581COMMIT" - "\u2581AWAKENED" - "\u2581TWILIGHT" - FFE - "\u2581PROVIDENCE" - "\u2581DENIED" - "\u2581BARGAIN" - "\u2581COMBAT" - "\u2581GREETING" - "\u2581SYMBOL" - "\u2581SHEPHERD" - "\u2581FOOTSTEPS" - "\u2581WROUGHT" - "\u2581MECHANICAL" - "\u2581LATIN" - "\u2581DEPOSIT" - "\u2581KU" - "\u2581PROMOT" - "\u2581SPANIARD" - "\u2581INTRODUCTION" - "\u2581PREPARING" - "\u2581MASSES" - "\u2581DIVERS" - "\u2581VELVET" - "\u2581NARRATIVE" - "\u2581AWOKE" - "\u2581CANDID" - "\u2581DISPUTE" - "\u2581APPETITE" - "\u2581PREFERRED" - "\u2581REDUCED" - "\u2581EASIER" - "\u2581ENCLOS" - "\u2581SCARLET" - "\u2581PERPETUAL" - "\u2581RESEMBLE" - "\u2581ELEPHANT" - "\u2581DISCIPLINE" - "\u2581SPECIMEN" - "\u2581VIRGIN" - "\u2581SHILLING" - "\u2581SOLICIT" - "\u2581RESPONSIBLE" - "\u2581COUCH" - "\u2581EGYPT" - "\u2581UNIVERSITY" - "\u2581ASCERTAIN" - "\u2581PEAK" - "\u2581RUSSIA" - "\u2581RESPONSIBILITY" - "\u2581CAPACITY" - "\u2581JACOB" - "\u2581KH" - "\u2581TUNE" - "\u2581STOPPING" - "\u</code></pre>