Other Open Access

ESPnet2 pretrained model, Shinji Watanabe/librispeech_asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best, fs=16k, lang=en

Shinji Watanabe


DataCite XML Export

<?xml version='1.0' encoding='utf-8'?>
<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.5281/zenodo.3966501</identifier>
  <creators>
    <creator>
      <creatorName>Shinji Watanabe</creatorName>
    </creator>
  </creators>
  <titles>
    <title>ESPnet2 pretrained model, Shinji Watanabe/librispeech_asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best, fs=16k, lang=en</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>ESPnet</subject>
    <subject>deep-learning</subject>
    <subject>python</subject>
    <subject>pytorch</subject>
    <subject>speech-recognition</subject>
    <subject>speech-synthesis</subject>
    <subject>speech-translation</subject>
    <subject>machine-translation</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-07-29</date>
  </dates>
  <resourceType resourceTypeGeneral="Other"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3966501</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsSupplementTo">https://github.com/espnet/espnet</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3966500</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">This model was trained by Shinji Watanabe using librispeech recipe in &lt;a href="https://github.com/espnet/espnet/"&gt;espnet&lt;/a&gt;.
&lt;p&gt;&amp;nbsp;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Python API&lt;/strong&gt;&lt;pre&gt;&lt;code class="language-python"&gt;See https://github.com/espnet/espnet_model_zoo&lt;/code&gt;&lt;/pre&gt;&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Evaluate in the recipe&lt;/strong&gt;&lt;pre&gt;&lt;code class="language-bash"&gt;git clone https://github.com/espnet/espnet
cd espnet
git checkout fca1edc18f8235c1de13925147519e6ecd03ec96
pip install -e .
cd egs2/librispeech/asr1
./run.sh --skip_data_prep false --skip_train true --download_model Shinji Watanabe/librispeech_asr_train_asr_transformer_e18_raw_bpe_sp_valid.acc.best&lt;/code&gt;
&lt;/pre&gt;&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Results&lt;/strong&gt;&lt;pre&gt;&lt;code&gt;
# 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|&lt;/code&gt;&lt;/pre&gt;&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;ASR config&lt;/strong&gt;&lt;pre&gt;&lt;code&gt;config: conf/tuning/train_asr_transformer_e18.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_asr_transformer_e18_raw_bpe_sp
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: 4
dist_rank: 3
local_rank: 3
dist_master_addr: localhost
dist_master_port: 33643
dist_launcher: null
multiprocessing_distributed: true
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 100
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_noise: false
accum_grad: 6
no_forward_run: false
resume: true
train_dtype: float32
log_interval: null
pretrain_path: []
pretrain_key: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 15000000
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:
- 
- 
- "\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"
- "\u2581BLAST"
- "\u2581CRIMSON"
- "\u2581DUMB"
- "\u2581GOSPEL"
- "\u2581SOLITUDE"
- "\u2581HAMMER"
- "\u2581ACCENT"
- "\u2581CONTACT"
- "\u2581DEPRIV"
- "\u2581RETIRE"
- "\u2581TRIUMPHANT"
- "\u2581THRONG"
- "\u2581ESCORT"
- "\u2581NICK"
- "\u2581NEIGHBOURHOOD"
- "\u2581TWAS"
- "\u2581OAR"
- "\u2581HOUND"
- "\u2581NEPHEW"
- "\u2581FUNERAL"
- "\u2581RECEIVING"
- "\u2581PLUCK"
- "\u2581TRENCH"
- "\u2581REPOSE"
- "\u2581PORCH"
- "\u2581DESPITE"
- "\u2581LINCOLN"
- "\u2581ZI"
- "\u2581REC</description>
  </descriptions>
</resource>
633
157
views
downloads
All versions This version
Views 633633
Downloads 157157
Data volume 159.7 GB159.7 GB
Unique views 562562
Unique downloads 108108

Share

Cite as