espnet audio automatic-speech-recognition en dataset:librispeech arxiv:1804.00015 license:cc-by-4.0 region:us
---
datasets:
- librispeech
language: en
license: cc-by-4.0
tags:
- espnet
- audio
- automatic-speech-recognition
---

## ESPnet2 ASR model

### `espnet/simpleoier_ls960_asr2_e_branchformer1_conv1d3_1gpu_raw_wavlm_large_21_km1k_bpe_rm5k_bpe_ts5k_sp`

This model was trained by simpleoier using librispeech recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
if you haven't done that already.

```bash
cd espnet
git checkout 161e4bb5092b77361fcb22e28691d028ef7a7194
pip install -e .
cd egs2/librispeech/asr2
./run.sh --skip_data_prep false --skip_train true --download_model espnet/simpleoier_ls960_asr2_e_branchformer1_conv1d3_1gpu_raw_wavlm_large_21_km1k_bpe_rm5k_bpe_ts5k_sp
```

<!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Fri Jun 23 10:16:00 CDT 2023`
- python version: `3.9.16 (main, May 15 2023, 23:46:34)  [GCC 11.2.0]`
- espnet version: `espnet 202304`
- pytorch version: `pytorch 1.13.1`
- Git hash: `ac5ffad321c64cbf159e4b789dbe26c43dc31b0e`
  - Commit date: `Wed Jun 14 19:50:52 2023 +0000`

## exp/asr_train_discrete_asr_e_branchformer1_conv1d3_1gpu_raw_wavlm_large_21_km1000_bpe_rm5000_bpe_ts5000_sp
### WER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_clean|2703|54402|97.8|1.9|0.2|0.3|2.4|30.0|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_other|2864|50948|95.6|4.0|0.4|0.4|4.8|43.8|
|decode_ctc0.3_asr_model_valid.acc.ave/test_clean|2620|52576|97.8|1.9|0.3|0.3|2.5|30.2|
|decode_ctc0.3_asr_model_valid.acc.ave/test_other|2939|52343|95.6|4.0|0.3|0.5|4.8|46.3|

### CER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_clean|2703|288456|99.4|0.3|0.3|0.2|0.8|30.0|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_other|2864|265951|98.4|0.9|0.7|0.5|2.1|43.8|
|decode_ctc0.3_asr_model_valid.acc.ave/test_clean|2620|281530|99.4|0.3|0.3|0.2|0.8|30.2|
|decode_ctc0.3_asr_model_valid.acc.ave/test_other|2939|272758|98.6|0.8|0.6|0.5|1.9|46.3|

### TER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_clean|2703|68010|97.2|1.9|0.9|0.3|3.1|30.0|
|decode_ctc0.3_asr_model_valid.acc.ave/dev_other|2864|63110|94.3|4.2|1.5|0.8|6.5|43.8|
|decode_ctc0.3_asr_model_valid.acc.ave/test_clean|2620|65818|97.1|1.9|1.0|0.3|3.2|30.2|
|decode_ctc0.3_asr_model_valid.acc.ave/test_other|2939|65101|94.4|3.8|1.7|0.7|6.3|46.3|

## ASR config

<details><summary>expand</summary>

```
config: conf/tuning/train_discrete_asr_e_branchformer1_conv1d3_1gpu.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_discrete_asr_e_branchformer1_conv1d3_1gpu_raw_wavlm_large_21_km1000_bpe_rm5000_bpe_ts5000_sp
ngpu: 1
seed: 0
num_workers: 4
num_att_plot: 1
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: 0
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 35
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 10
nbest_averaging_interval: 0
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: true
log_interval: 1000
use_matplotlib: true
use_tensorboard: true
create_graph_in_tensorboard: false
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 420000000
valid_batch_bins: null
train_shape_file:
- exp/asr_stats_raw_rm_wavlm_large_21_km1000_bpe5000_bpe5000_sp/train/text_shape.bpe
- exp/asr_stats_raw_rm_wavlm_large_21_km1000_bpe5000_bpe5000_sp/train/src_text_shape.bpe
valid_shape_file:
- exp/asr_stats_raw_rm_wavlm_large_21_km1000_bpe5000_bpe5000_sp/valid/text_shape.bpe
- exp/asr_stats_raw_rm_wavlm_large_21_km1000_bpe5000_bpe5000_sp/valid/src_text_shape.bpe
batch_type: numel
valid_batch_type: null
fold_length:
- 200
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
chunk_excluded_key_prefixes: []
train_data_path_and_name_and_type:
-   - dump/raw/train_960_sp/text.ts.en
    - text
    - text
-   - dump/raw/train_960_sp/text.rm.wavlm_large_21_km1000
    - src_text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/dev/text.ts.en
    - text
    - text
-   - dump/raw/dev/text.rm.wavlm_large_21_km1000
    - src_text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
exclude_weight_decay: false
exclude_weight_decay_conf: {}
optim: adam
optim_conf:
    lr: 0.006
    weight_decay: 1.0e-06
scheduler: warmuplr
scheduler_conf:
    warmup_steps: 15000
token_list:
- <blank>
- <unk>
- ▁THE
- S
- ▁AND
- ▁OF
- ▁TO
- ▁A
- ▁IN
- ▁I
- ▁HE
- ▁THAT
- ▁WAS
- ED
- ▁IT
- ''''
- ▁HIS
- ING
- ▁YOU
- ▁WITH
- ▁FOR
- ▁HAD
- T
- ▁AS
- ▁HER
- ▁IS
- ▁BE
- ▁BUT
- ▁NOT
- ▁SHE
- D
- ▁AT
- ▁ON
- LY
- ▁HIM
- ▁THEY
- ▁ALL
- ▁HAVE
- ▁BY
- ▁SO
- ▁THIS
- ▁MY
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- ▁ME
- ▁SAID
- ▁FROM
- ▁ONE
- Y
- E
- ▁WERE
- ▁WE
- ▁NO
- N
- ▁THERE
- ▁OR
- ER
- ▁AN
- ▁WHEN
- ▁ARE
- ▁THEIR
- ▁WOULD
- ▁IF
- ▁WHAT
- ▁THEM
- ▁WHO
- ▁OUT
- M
- ▁DO
- ▁WILL
- ▁UP
- ▁BEEN
- P
- R
- ▁MAN
- ▁THEN
- ▁COULD
- ▁MORE
- C
- ▁INTO
- ▁NOW
- ▁VERY
- ▁YOUR
- ▁SOME
- ▁LITTLE
- ES
- ▁TIME
- RE
- ▁CAN
- ▁LIKE
- LL
- ▁ABOUT
- ▁HAS
- ▁THAN
- ▁DID
- ▁UPON
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- IN
- ▁ANY
- ▁WELL
- ▁ONLY
- B
- ▁SEE
- ▁GOOD
- ▁OTHER
- ▁TWO
- L
- ▁KNOW
- ▁GO
- ▁DOWN
- ▁BEFORE
- A
- AL
- ▁OUR
- ▁OLD
- ▁SHOULD
- ▁MADE
- ▁AFTER
- ▁GREAT
- ▁DAY
- ▁MUST
- ▁COME
- ▁HOW
- ▁SUCH
- ▁CAME
- LE
- ▁WHERE
- ▁US
- ▁NEVER
- ▁THESE
- ▁MUCH
- ▁DE
- ▁MISTER
- ▁WAY
- G
- ▁S
- ▁MAY
- ATION
- ▁LONG
- OR
- ▁AM
- ▁FIRST
- ▁BACK
- ▁OWN
- ▁RE
- ▁AGAIN
- ▁SAY
- ▁MEN
- ▁WENT
- ▁HIMSELF
- ▁HERE
- NESS
- ▁THINK
- V
- IC
- ▁EVEN
- ▁THOUGHT
- ▁HAND
- ▁JUST
- ▁O
- ▁UN
- VE
- ION
- ▁ITS
- 'ON'
- ▁MAKE
- ▁MIGHT
- ▁TOO
- K
- ▁AWAY
- ▁LIFE
- TH
- ▁WITHOUT
- ST
- ▁THROUGH
- ▁MOST
- ▁TAKE
- ▁DON
- ▁EVERY
- F
- O
- ▁SHALL
- ▁THOSE
- ▁EYES
- AR
- ▁STILL
- ▁LAST
- ▁HOUSE
- ▁HEAD
- ABLE
- ▁NOTHING
- ▁NIGHT
- ITY
- ▁LET
- ▁MANY
- ▁OFF
- ▁BEING
- ▁FOUND
- ▁WHILE
- EN
- ▁SAW
- ▁GET
- ▁PEOPLE
- ▁FACE
- ▁YOUNG
- CH
- ▁UNDER
- ▁ONCE
- ▁TELL
- AN
- ▁THREE
- ▁PLACE
- ▁ROOM
- ▁YET
- ▁SAME
- IL
- US
- U
- ▁FATHER
- ▁RIGHT
- EL
- ▁THOUGH
- ▁ANOTHER
- LI
- RI
- ▁HEART
- IT
- ▁PUT
- ▁TOOK
- ▁GIVE
- ▁EVER
- ▁E
- ▁PART
- ▁WORK
- ERS
- ▁LOOK
- ▁NEW
- ▁KING
- ▁MISSUS
- ▁SIR
- ▁LOVE
- ▁MIND
- ▁LOOKED
- W
- RY
- ▁ASKED
- ▁LEFT
- ET
- ▁LIGHT
- CK
- ▁DOOR
- ▁MOMENT
- RO
- ▁WORLD
- ▁THINGS
- ▁HOME
- UL
- ▁THING
- LA
- ▁WHY
- ▁MOTHER
- ▁ALWAYS
- ▁FAR
- FUL
- ▁WATER
- CE
- IVE
- UR
- ▁HEARD
- ▁SOMETHING
- ▁SEEMED
- I
- LO
- ▁BECAUSE
- OL
- ▁END
- ▁TOLD
- ▁CON
- ▁YES
- ▁GOING
- ▁GOT
- RA
- IR
- ▁WOMAN
- ▁GOD
- EST
- TED
- ▁FIND
- ▁KNEW
- ▁SOON
- ▁EACH
- ▁SIDE
- H
- TON
- MENT
- ▁OH
- NE
- Z
- LING
- ▁AGAINST
- TER
- ▁NAME
- ▁MISS
- ▁QUITE
- ▁WANT
- ▁YEARS
- ▁FEW
- ▁BETTER
- ENT
- ▁HALF
- ▁DONE
- ▁ALSO
- ▁BEGAN
- ▁HAVING
- ▁ENOUGH
- IS
- ▁LADY
- ▁WHOLE
- LESS
- ▁BOTH
- ▁SEEN
- ▁SET
- ▁WHITE
- ▁COURSE
- IES
- ▁VOICE
- ▁CALLED
- ▁D
- ▁EX
- ATE
- ▁TURNED
- ▁GAVE
- ▁C
- ▁POOR
- MAN
- UT
- NA
- ▁DEAR
- ISH
- ▁GIRL
- ▁MORNING
- ▁BETWEEN
- LED
- ▁NOR
- IA
- ▁AMONG
- MA
- ▁
- ▁SMALL
- ▁REST
- ▁WHOM
- ▁FELT
- ▁HANDS
- ▁MYSELF
- ▁HIGH
- ▁M
- ▁HOWEVER
- ▁HERSELF
- ▁P
- CO
- ▁STOOD
- ID
- ▁KIND
- ▁HUNDRED
- AS
- ▁ROUND
- ▁ALMOST
- TY
- ▁SINCE
- ▁G
- AM
- ▁LA
- SE
- ▁BOY
- ▁MA
- ▁PERHAPS
- ▁WORDS
- ATED
- ▁HO
- X
- ▁MO
- ▁SAT
- ▁REPLIED
- ▁FOUR
- ▁ANYTHING
- ▁TILL
- ▁UNTIL
- ▁BLACK
- TION
- ▁CRIED
- RU
- TE
- ▁FACT
- ▁HELP
- ▁NEXT
- ▁LOOKING
- ▁DOES
- ▁FRIEND
- ▁LAY
- ANCE
- ▁POWER
- ▁BROUGHT
- VER
- ▁FIRE
- ▁KEEP
- PO
- FF
- ▁COUNTRY
- ▁SEA
- ▁WORD
- ▁CAR
- ▁DAYS
- ▁TOGETHER
- ▁IMP
- ▁REASON
- KE
- ▁INDEED
- TING
- ▁MATTER
- ▁FULL
- ▁TEN
- TIC
- ▁LAND
- ▁RATHER
- ▁AIR
- ▁HOPE
- ▁DA
- ▁OPEN
- ▁FEET
- ▁EN
- ▁FIVE
- ▁POINT
- ▁CO
- OM
- ▁LARGE
- ▁B
- ▁CL
- ME
- ▁GONE
- ▁CHILD
- INE
- GG
- ▁BEST
- ▁DIS
- UM
- ▁HARD
- ▁LORD
- OUS
- ▁WIFE
- ▁SURE
- ▁FORM
- DE
- ▁DEATH
- ANT
- ▁NATURE
- ▁BA
- ▁CARE
- ▁BELIEVE
- PP
- ▁NEAR
- ▁RO
- ▁RED
- ▁WAR
- IE
- ▁SPEAK
- ▁FEAR
- ▁CASE
- ▁TAKEN
- ▁ALONG
- ▁CANNOT
- ▁HEAR
- ▁THEMSELVES
- CI
- ▁PRESENT
- AD
- ▁MASTER
- ▁SON
- ▁THUS
- ▁LI
- ▁LESS
- ▁SUN
- ▁TRUE
- IM
- IOUS
- ▁THOUSAND
- ▁MONEY
- ▁W
- ▁BEHIND
- ▁CHILDREN
- ▁DOCTOR
- AC
- ▁TWENTY
- ▁WISH
- ▁SOUND
- ▁WHOSE
- ▁LEAVE
- ▁ANSWERED
- ▁THOU
- ▁DUR
- ▁HA
- ▁CERTAIN
- ▁PO
- ▁PASSED
- GE
- TO
- ▁ARM
- ▁LO
- ▁STATE
- ▁ALONE
- TA
- ▁SHOW
- ▁NEED
- ▁LIVE
- ND
- ▁DEAD
- ENCE
- ▁STRONG
- ▁PRE
- ▁TI
- ▁GROUND
- SH
- TI
- ▁SHORT
- IAN
- UN
- ▁PRO
- ▁HORSE
- MI
- ▁PRINCE
- ARD
- ▁FELL
- ▁ORDER
- ▁CALL
- AT
- ▁GIVEN
- ▁DARK
- ▁THEREFORE
- ▁CLOSE
- ▁BODY
- ▁OTHERS
- ▁SENT
- ▁SECOND
- ▁OFTEN
- ▁CA
- ▁MANNER
- MO
- NI
- ▁BRING
- ▁QUESTION
- ▁HOUR
- ▁BO
- AGE
- ▁ST
- ▁TURN
- ▁TABLE
- ▁GENERAL
- ▁EARTH
- ▁BED
- ▁REALLY
- ▁SIX
- 'NO'
- IST
- ▁BECOME
- ▁USE
- ▁READ
- ▁SE
- ▁VI
- ▁COMING
- ▁EVERYTHING
- ▁EM
- ▁ABOVE
- ▁EVENING
- ▁BEAUTIFUL
- ▁FEEL
- ▁RAN
- ▁LEAST
- ▁LAW
- ▁ALREADY
- ▁MEAN
- ▁ROSE
- WARD
- ▁ITSELF
- ▁SOUL
- ▁SUDDENLY
- ▁AROUND
- RED
- ▁ANSWER
- ICAL
- ▁RA
- ▁WIND
- ▁FINE
- ▁WON
- ▁WHETHER
- ▁KNOWN
- BER
- NG
- ▁TA
- ▁CAPTAIN
- ▁EYE
- ▁PERSON
- ▁WOMEN
- ▁SORT
- ▁ASK
- ▁BROTHER
- ▁USED
- ▁HELD
- ▁BIG
- ▁RETURNED
- ▁STRANGE
- ▁BU
- ▁PER
- ▁FREE
- ▁EITHER
- ▁WITHIN
- ▁DOUBT
- ▁YEAR
- ▁CLEAR
- ▁SIGHT
- ▁GRA
- ▁LOST
- ▁KEPT
- ▁F
- PE
- ▁BAR
- ▁TOWN
- ▁SLEEP
- ARY
- ▁HAIR
- ▁FRIENDS
- ▁DREAM
- ▁FELLOW
- PER
- ▁DEEP
- QUE
- ▁BECAME
- ▁REAL
- ▁PAST
- ▁MAKING
- RING
- ▁COMP
- ▁ACT
- ▁BAD
- HO
- STER
- ▁YE
- ▁MEANS
- ▁RUN
- MEN
- ▁DAUGHTER
- ▁SENSE
- ▁CITY
- ▁SOMETIMES
- ▁TOWARDS
- ▁ROAD
- ▁SP
- ▁LU
- ▁READY
- ▁FOOT
- ▁COLD
- ▁SA
- ▁LETTER
- ▁ELSE
- ▁MAR
- ▁STA
- BE
- ▁TRUTH
- ▁LE
- BO
- ▁BUSINESS
- CHE
- ▁JOHN
- ▁SUBJECT
- ▁COURT
- ▁IDEA
- ILY
- ▁RIVER
- ATING
- ▁FAMILY
- HE
- ▁DIDN
- ▁GLAD
- ▁SEVERAL
- IAL
- ▁UNDERSTAND
- ▁SC
- ▁POSSIBLE
- ▁DIFFERENT
- ▁RETURN
- ▁ARMS
- ▁LOW
- ▁HOLD
- ▁TALK
- ▁RU
- ▁WINDOW
- ▁INTEREST
- ▁SISTER
- SON
- ▁SH
- ▁BLOOD
- ▁SAYS
- ▁CAP
- ▁DI
- ▁HUMAN
- ▁CAUSE
- NCE
- ▁THANK
- ▁LATE
- GO
- ▁CUT
- ▁ACROSS
- ▁STORY
- NT
- ▁COUNT
- ▁ABLE
- DY
- LEY
- ▁NUMBER
- ▁STAND
- ▁CHURCH
- ▁THY
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- LES
- BLE
- OP
- ▁EFFECT
- BY
- ▁K
- ▁NA
- ▁SPOKE
- ▁MET
- ▁GREEN
- ▁HUSBAND
- ▁RESPECT
- ▁PA
- ▁FOLLOWED
- ▁REMEMBER
- ▁LONGER
- ▁AGE
- ▁TAKING
- ▁LINE
- ▁SEEM
- ▁HAPPY
- LAND
- EM
- ▁STAY
- ▁PLAY
- ▁COMMON
- ▁GA
- ▁BOOK
- ▁TIMES
- ▁OBJECT
- ▁SEVEN
- QUI
- DO
- UND
- ▁FL
- ▁PRETTY
- ▁FAIR
- WAY
- ▁WOOD
- ▁REACHED
- ▁APPEARED
- ▁SWEET
- ▁FALL
- BA
- ▁PASS
- ▁SIGN
- ▁TREE
- IONS
- ▁GARDEN
- ▁ILL
- ▁ART
- ▁REMAIN
- ▁OPENED
- ▁BRIGHT
- ▁STREET
- ▁TROUBLE
- ▁PAIN
- ▁CONTINUED
- ▁SCHOOL
- OUR
- ▁CARRIED
- ▁SAYING
- HA
- ▁CHANGE
- ▁FOLLOW
- ▁GOLD
- ▁SW
- ▁FEELING
- ▁COMMAND
- ▁BEAR
- ▁CERTAINLY
- ▁BLUE
- ▁NE
- CA
- ▁WILD
- ▁ACCOUNT
- ▁OUGHT
- UD
- ▁T
- ▁BREATH
- ▁WANTED
- ▁RI
- ▁HEAVEN
- ▁PURPOSE
- ▁CHARACTER
- ▁RICH
- ▁PE
- ▁DRESS
- OS
- FA
- ▁TH
- ▁ENGLISH
- ▁CHANCE
- ▁SHIP
- ▁VIEW
- ▁TOWARD
- AK
- ▁JOY
- ▁JA
- ▁HAR
- ▁NEITHER
- ▁FORCE
- ▁UNCLE
- DER
- ▁PLAN
- ▁PRINCESS
- DI
- ▁CHIEF
- ▁HAT
- ▁LIVED
- ▁AB
- ▁VISIT
- ▁MOR
- TEN
- ▁WALL
- UC
- ▁MINE
- ▁PLEASURE
- ▁SMILE
- ▁FRONT
- ▁HU
- ▁DEAL
- OW
- ▁FURTHER
- GED
- ▁TRIED
- DA
- VA
- ▁NONE
- ▁ENTERED
- ▁QUEEN
- ▁PAY
- ▁EL
- ▁EXCEPT
- ▁SHA
- ▁FORWARD
- ▁EIGHT
- ▁ADDED
- ▁PUBLIC
- ▁EIGHTEEN
- ▁STAR
- ▁HAPPENED
- ▁LED
- ▁WALKED
- ▁ALTHOUGH
- ▁LATER
- ▁SPIRIT
- ▁WALK
- ▁BIT
- ▁MEET
- LIN
- ▁FI
- LT
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- ▁CONFUSION
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- ▁CONCEIVE
- ▁PRIZE
- ▁JESUS
- ▁ADDITION
- ▁RUDE
- ▁FATAL
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- ▁AFFECTED
- ▁DIRECTED
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- ▁TY
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- ▁RECOVERED
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- ▁AGENT
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- ▁INCLINED
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- HU
- ▁ENORMOUS
- ▁RESTRAIN
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- TTERED
- ▁POLE
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- ▁EXCEPTION
- ▁INTIMATE
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- CAST
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- ▁LOCKED
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- ▁CONNECTED
- ▁ASSURE
- ▁COCK
- ▁UTMOST
- ▁DEVOTED
- ▁RELI
- ▁SUFFICIENTLY
- ▁INTELLECTUAL
- ▁CARPET
- ▁OBJECTION
- ▁AFTERWARD
- ▁REALITY
- ▁NEGRO
- ▁RETAIN
- ▁ASCEND
- ▁CEASE
- ▁KATE
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- KO
- ▁BOND
- MOST
- ▁COAL
- GATE
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- ▁NORTHERN
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- ▁STARTLED
- ▁STATEMENT
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- ▁NERVE
- ▁INSPECT
- ▁INDUCE
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- ▁DATE
- ▁AMBITION
- ▁SLOPE
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- ▁CREATED
- ▁CONTINUALLY
- ▁LIGHTNING
- ▁BORNE
- ▁TOTAL
- ▁DISPOSED
- ▁RIFLE
- ▁POLLY
- ▁GOAT
- ▁BACKWARD
- ▁VIRGINIA
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- ▁GLORIOUS
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- ▁RESIGN
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- ▁DISCUSSION
- ▁VENTURED
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- ▁SCALE
- ▁STAFF
- ▁ENTREAT
- ▁FAREWELL
- ▁LUNCH
- ▁PEEP
- ▁MULE
- ▁SOMEONE
- ▁DISAPPEAR
- ▁DECISION
- ▁PISTOL
- ▁PUN
- ▁SPUR
- ▁ASSUMED
- ▁EXTEND
- ▁ENTHUSIASM
- ▁DEFINITE
- ▁UNDERTAKE
- ▁COMMITTEE
- ▁SIMON
- ▁FENCE
- ▁APPLIED
- ▁RELATED
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- ▁CLOAK
- ▁HUMANITY
- ▁FAMILIES
- ▁PHILOSOPHER
- ▁DWARF
- ▁OVERCOME
- ▁DEFEAT
- ▁FASTENED
- ▁MARSH
- ▁CLASSES
- ▁TOMB
- ▁GRACIOUS
- ▁REMOTE
- ▁CELL
- ▁SHRIEK
- ▁RESCUE
- ▁POOL
- ▁ORGANIZ
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- ▁BORDER
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- ▁EMILY
- ▁JEST
- ▁PLAC
- ▁WEIGH
- ▁ASSOCIATE
- ▁GLIMPSE
- ▁STUCK
- ▁BOLT
- ▁MURDERER
- ▁PONY
- ▁DISTINGUISH
- ▁INSTITUTION
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- ▁COMPLIMENT
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- ▁FEEBLE
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- MONT
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- ▁INCLINATION
- ▁BEHAVE
- ▁SUSAN
- ▁DISTINCTION
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- ▁ELBOW
- ▁GAZING
- ▁CONSUM
- ▁SPIN
- ▁OATH
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- ▁CHARACTERISTIC
- ▁SPEAR
- ▁SLAIN
- ▁SAUCE
- ▁FROG
- ▁CONCEPTION
- ▁TIMID
- ▁ZEAL
- ▁APPARENT
- SHIRE
- ▁CENTER
- ▁VARIETY
- ▁DUSK
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- ▁COLUMN
- ▁REVENGE
- ▁RIVAL
- ▁IMITAT
- ▁PASSIONATE
- ▁SELFISH
- ▁NORMAN
- ▁REPAIR
- ▁THRILL
- ▁TREATMENT
- ▁ROSA
- ▁MARTIN
- ▁INDIFFERENT
- ▁THITHER
- ▁GALLANT
- ▁PEPPER
- ▁RECOLLECT
- ▁VINE
- ▁SCARCE
- ▁SHIELD
- ▁MINGLED
- CLOSE
- ▁HARSH
- ▁BRICK
- ▁HUMOR
- ▁MISCHIEF
- ▁TREMENDOUS
- ▁FUNCTION
- ▁SMART
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- ▁DISMISS
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- ▁WHISTLE
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- ▁REFERENCE
- ▁DUCK
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- ▁PURSE
- ▁PARTNER
- ▁PROPHET
- ▁SHIVER
- ▁NEIGHBOURHOOD
- ▁REPRESENTATIVE
- SAIL
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- ▁ACQUIRED
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- ▁DOCTRINE
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- ▁ANGLE
- ▁MAJORITY
- ▁AUTUMN
- ▁CONFUSED
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- ▁ACHIEVE
- ▁DISGUISE
- ▁REDUCED
- ▁EARLIER
- ▁THEATRE
- ▁DECIDE
- MINATED
- OLOGICAL
- ▁OCCUPATION
- ▁VIGOROUS
- ▁CONTINENT
- ▁DECLINE
- ▁COMMUNITY
- ▁MOTIONLESS
- ▁HATRED
- ▁COMMUNICATION
- ▁BOWL
- ▁COMMENT
- ▁APPROVE
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- ▁SCIENTIFIC
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- ▁SHIFT
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- ▁CONTRAST
- ▁AMUSEMENT
- ▁PLOT
- ▁LYN
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- ▁SNATCH
- ▁UNCERTAIN
- ▁PRESSURE
- ▁PERCH
- ▁APPLY
- ▁PLANET
- ▁NOTWITHSTANDING
- ▁SWUNG
- ▁STIRRED
- ▁ATTENDANT
- ▁ENJOYMENT
- ▁WORRY
- ▁ALBERT
- ▁NAKED
- ▁TALENT
- ▁MARIAN
- ▁REFORM
- ▁DELIBERATE
- ▁INTELLIGENT
- ▁SENSITIVE
- ▁YONDER
- ▁PUPIL
- ▁FRIGHTFUL
- ▁DOUBTFUL
- ▁STANDARD
- ▁MAGISTRATE
- ▁SHEPHERD
- ▁STOMACH
- ▁DEPOSIT
- ▁RENEW
- ▁HEDGE
- ▁FRANCS
- ▁POSSIBILITY
- ▁RESEMBLE
- ▁FATIGUE
- ▁PORTRAIT
- ▁FAVORITE
- ▁CREAM
- ▁BURG
- ▁SECRETARY
- ▁DIVERS
- ▁ACTIVITY
- ▁SPECULAT
- ▁HUMOUR
- ▁FITTED
- ▁EXTERNAL
- ▁CETERA
- ▁WRAPPED
- ▁WHIT
- ▁FRED
- ▁EXAMINATION
- ▁LODGING
- ▁OWING
- ▁JAW
- ▁CROW
- ▁BALANCE
- ▁PUFF
- ▁TENDERNESS
- ▁PORTHOS
- ▁ANCHOR
- ▁INTERRUPT
- ▁NECESSARILY
- ▁PERPETUAL
- ▁AGONY
- ▁POPE
- ▁SCHOLAR
- ▁SCOTLAND
- ▁SUPPRESS
- ▁WRATH
- ▁WRECK
- ▁EXCEED
- ▁PERFECTION
- ▁INDIA
- ▁TRADITION
- ▁SECTION
- ▁EASTERN
- ▁DOORWAY
- ▁WIVES
- ▁CONVENTION
- ▁ANNOUNC
- ▁EGYPT
- ▁CONTRADICT
- ▁SCRATCH
- ▁CENTRAL
- ▁GLOVE
- ▁WAX
- ▁PREPARE
- ▁ACCOMPANY
- ▁INCREASING
- ▁LIBERAL
- ▁RAISING
- ▁ORANGE
- ▁SHOE
- ▁ATTRIBUTE
- ▁LITERATURE
- ▁PUZZLED
- ▁WITHDRAW
- ▁WHITHER
- ▁HAWK
- ▁MOONLIGHT
- ▁EXAMINE
- ▁HAPPILY
- ▁PRECEDE
- ▁DETECTIVE
- ▁INCHES
- ▁SOLITARY
- ▁DUTCH
- ▁NAPOLEON
- ▁UNEASY
- ▁CARDINAL
- ▁BLEW
- ▁FOWL
- ▁DECORAT
- ▁CHILDHOOD
- ▁TORMENT
- ▁LOSING
- ▁PERMISSION
- ▁BLANK
- ▁UPSTAIRS
- ▁CAPACITY
- ▁TRIFLE
- ▁FOLLY
- ▁RECOGNIZE
- ▁REMOVE
- ▁VENGEANCE
- ▁ENTERPRISE
- ▁BEDROOM
- ▁ANYHOW
- ▁INQUIRY
- ▁ASHES
- ▁DRAG
- ▁HUSH
- ▁AWKWARD
- ▁SATURDAY
- ▁GENUINE
- ▁SURVIV
- ▁SKIRT
- ▁AFFECTIONATE
- ▁TANG
- ▁MUTUAL
- ▁DISPUTE
- ▁EAGLE
- ▁INCOME
- ▁BIND
- ▁FAME
- ▁IMPROVEMENT
- ROVING
- ▁DIFFER
- ▁AWOKE
- ▁SLEEVE
- ▁SOLITUDE
- ▁FAVOURITE
- JI
- ▁DETECT
- ▁COMPREHEND
- ▁PREPARING
- ▁SERPENT
- ▁SUMMIT
- ▁KNOT
- ▁KNIT
- ▁COPY
- ▁STOPPING
- ▁FADED
- ▁HIDEOUS
- ▁JULIE
- STEAD
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- ▁CONFLICT
- ▁PROPOSITION
- ▁REFUGE
- ▁GALLERY
- ▁BUNDLE
- ▁AXE
- ▁SLAVERY
- ▁MASK
- ▁ALYOSHA
- ▁LADDER
- ▁DEPARTMENT
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- ▁DEPRESS
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- ▁SCARLET
- ▁KITTY
- ▁RECEIVING
- ▁SURRENDER
- ▁SUSTAIN
- ▁TWILIGHT
- ▁CONGRESS
- ▁IRELAND
- ▁FUNNY
- ▁LEND
- ▁CONSTITUTE
- ▁FUNERAL
- ▁CRYSTAL
- ▁SPAIN
- ▁EXCEEDINGLY
- ▁DAMN
- ▁COMMUN
- ▁CIVILIZATION
- ▁PREJUDICE
- ▁PORCH
- ▁ASSISTANT
- ▁INDUSTRY
- ▁TUMBLE
- ▁DEFENCE
- ▁HITHER
- ▁SMOT
- ▁COLONI
- ▁AMAZEMENT
- ▁MARGUERITE
- ▁MIRACLE
- ▁INHERIT
- ▁BEGGAR
- ▁ENVELOPE
- ▁INDIGNATION
- ▁NATASHA
- ▁PROPOSAL
- ▁FRAGMENT
- ▁ROUSED
- ▁ROAST
- ENCIES
- ▁COMMENCED
- ▁RESOURCE
- ▁POPULATION
- ▁QUOTH
- ▁PURSUE
- ▁EDUCAT
- ▁AFFLICT
- ▁CONTACT
- ▁CRIMSON
- ▁DIVISION
- ▁DISORDER
- ▁COPPER
- ▁SOLICIT
- ▁MODERATE
- ▁DRUM
- ▁SWIM
- ▁SALUTE
- ▁ASSUME
- ▁MUSCLE
- ▁OVERWHELM
- ▁SHAKESPEARE
- ▁STRUGGLING
- ▁TRANQUIL
- ▁CHICKEN
- ▁TREAD
- ▁CLAW
- ▁BIBLE
- ▁RIDGE
- ▁THREAT
- ▁VELVET
- ▁EXPOSED
- ▁IDIOT
- ▁BARREL
- ▁PENNY
- ▁TEMPTATION
- ▁DANGLARS
- ▁CENTURIES
- ▁DISTRIBUT
- ▁REJECT
- ▁RETORTED
- ▁CONCENTRAT
- ▁CORDIAL
- ▁MOTOR
- ▁CANNON
- KEEP
- ▁WRETCH
- ▁ASSURANCE
- ▁THIEF
- ▁SURVEY
- ▁VITAL
- ▁RAILWAY
- ▁JACKSON
- ▁CRASH
- ▁GROWL
- ▁COMBAT
- ▁RECOLLECTION
- ▁SECURITY
- ▁JACOB
- ▁CLUTCH
- ▁BLANKET
- ▁NANCY
- ▁CELLAR
- ▁CONVENIENT
- ▁INDIGNANT
- ▁COARSE
- ▁WORM
- ▁SCREEN
- ▁TRANSPORT
- ▁BULLET
- ▁APPRECIATE
- ▁DEVOTION
- ▁INVISIBLE
- ▁DRIED
- ▁MIXTURE
- ▁CANDID
- ▁PERFORMANCE
- ▁RIPE
- ▁EXQUISITE
- ▁BARGAIN
- ▁TOBACCO
- ▁LOYAL
- ▁MOULD
- ▁ATTENTIVE
- ▁DOROTHY
- ▁BRUTE
- ▁ESTABLISHMENT
- ▁ABILITY
- ▁INHABIT
- ▁OBSCURE
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- 佥僜债傪
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- 佢兗僯兘侺
- 关九俽亼
- 亯云俳产丰
- 冼伨件
- 侣乑佴傧
- 侂乳再
- 侉凤
- 冭丱儃何
- 偬供亱佺倒俵
- 倪估侔仉
- 亍傹
- 便侷儮亢俺
- 偠僮偠僮偠
- 减乹亣仄僟
- 儕伢俎冚他
- 侨
- 倿俎冚他儓
- 冨傄候
- 事伶
- 倜侹丩
- 僕乇丮
- 亨促冃
- 乒傕乱丑
- 也亰于丹
- 侜僑伷乐
- 付举净冻
- 乽
- 仏僝
- 傃俳乤产丰
- 严仨伔仪倌
- 儒傰
- 儎休兓侞
- 倖僄備假
- 伙傑佮
- 佘乳佘
- 伿僋倐假
- 偿僆佪俛
- 伪乱丑其
- 作倉修临仺
- 令傓乶伈侯偉
- 亯云乘俳产丰
- 倏
- 伏乹亣仄
- 倓俆儦
- 丕亿傇
- 佭七佃
- 仕凛
- 仼倔仼
- 伙傑倹佮
- 么亖么再
- 佅伶
- 会业伕
- 傔伺
- 倛么倛
- 伦僂仅
- 僃兠以体乯儖乮
- 低儀儭伨件
- 儞俲
- 些佦与傧
- 偯乌倃
- 偻傘亖
- 侌倄侌
- 儼乧
- 伫亘佁
- 丕傇公乄
- 串伪傕凛丑
- 了傌
- 丗俿偈丞
- 倁俋凛丑
- 偤儔二儦
- 傫傆伧個乊丒
- 儲
- 例侵伷兑
- 儹丢兡乆
- 使侷交亢俺
- 么倛再
- 俣倪估侔
- 凌俤乇丮
- 作倉修丫偘
- 仡兠乯佟亷
- 傎丵
- 丈伣
- 使侷兎儮亢
- 傊傞
- 么乳么亖么
- 仵举冒冻
- 佇倡业伕佬
- 偤亘亊儸
- 儼冎兊
- 傃俳伜乎
- 俞兩乩佺丙俵
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- 侣儊偆佴傧
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- 下侙书伩丫俰
- 冲冩么冩
- ▁丠互伟亦伟
- 傜丱亟僡
- ▁丠互亦伟
- 丏冕丽
- 健傞偎侔仉
- 况习侧僷
- 侥俿偈
- 仃亦亐冲冩
- 侰乞冨仑
- 伮兞伌
- 倁仕乱伀
- 傘乳僾俔倱
- 侌丕偋
- 伢代亥
- 丶亣仄僟
- 也仹
- 亣凋
- 俯
- 冀倛冀倛冀倛冀倛冀
- 业乓俠
- 仏们俤丮
- 兢乕佁
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- 候侇体催仔佞为
- 倖僄乶兺
- 佺亯偼乘
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- 临偘仺仃
- 仫偭
- 兟侁丅佦亳
- 侕僸倓侉亇侠
- 俭倓亇侠
- 冡伺佈亗七
- 乩享佺丙俵
- 傛亃侣
- 们俤乇丮兦
- 佑京价兩乩
- 仵凎冻
- 么不再
- 倥乳俊
- 兗僯丩乥
- 傃俳乤住儖
- 伮兞侓党
- 僚仾为
- 上冀上
- 儃何侧僷亶
- 丆倛丆倛
- 书伩
- 偒佴亍俤丮
- 傟傪乀
- 僓乳僓
- 丕乳丕傇
- 佞
- 充俹佪儩
- 亵僔亦冮
- 兵伢
- 乬僄備伻他
- 侽亮亀
- 冗傞伶
- 僕傆伧儽乊
- 冹佪减
- 倁仕乱伀其
- 乜傐丏
- 亠伌
- 册冃位
- 凔借傑倹佮
- 傿
- 伜傮亳
- 僔冮偠冮
- 儇侚偎丳
- 倓乓俠
- 兽仨伔
- 価儡丯
- 侙下侙书伩丫俰
- 况丷何乃
- 僥
- 倵
- 兣
- 傷
- 侾
- 全
- 凕
- 偩
- 僙
- 乎
- 児
- 从
- 凢
- 倽
- 兮
- 兒
- 俄
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- 久
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- 仸
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- 丠
- 任
- <sos/eos>
init: null
input_size: null
ctc_conf:
    dropout_rate: 0.0
    ctc_type: builtin
    reduce: true
    ignore_nan_grad: null
    zero_infinity: true
use_preprocessor: true
token_type: bpe
src_token_type: bpe
bpemodel: data/token_list/tgt_bpe_unigram5000_ts_en/bpe.model
src_bpemodel: data/token_list/src_bpe_unigram5000_rm_wavlm_large_21_km1000/bpe.model
non_linguistic_symbols: null
cleaner: null
g2p: null
tokenizer_encode_conf: null
src_tokenizer_encode_conf:
    enable_sampling: true
    alpha: 0.4
    nbest_size: -1
frontend: embed
frontend_conf:
    embed_dim: 512
    positional_dropout_rate: 0.1
specaug: specaug
specaug_conf:
    apply_time_warp: false
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: false
    freq_mask_width_range:
    - 0
    - 10
    num_freq_mask: 0
    apply_time_mask: true
    time_mask_width_ratio_range:
    - 0.0
    - 0.05
    num_time_mask: 10
preencoder: null
preencoder_conf: {}
encoder: e_branchformer
encoder_conf:
    output_size: 256
    attention_heads: 4
    attention_layer_type: rel_selfattn
    pos_enc_layer_type: rel_pos
    rel_pos_type: latest
    cgmlp_linear_units: 1024
    cgmlp_conv_kernel: 31
    use_linear_after_conv: false
    gate_activation: identity
    num_blocks: 12
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    attention_dropout_rate: 0.1
    input_layer: conv1d3
    layer_drop_rate: 0.0
    linear_units: 1024
    positionwise_layer_type: linear
    use_ffn: true
    macaron_ffn: true
    merge_conv_kernel: 31
postencoder: null
postencoder_conf: {}
decoder: transformer
decoder_conf:
    attention_heads: 4
    linear_units: 2048
    num_blocks: 6
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    self_attention_dropout_rate: 0.1
    src_attention_dropout_rate: 0.1
    layer_drop_rate: 0.0
model: discrete_asr
model_conf:
    ctc_weight: 0.3
    lsm_weight: 0.1
    length_normalized_loss: false
    share_decoder_input_output_embed: false
    share_encoder_decoder_input_embed: false
required:
- output_dir
- src_token_list
- token_list
version: '202304'
distributed: false
```

</details>



### Citing ESPnet

```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}




```

or arXiv:

```bibtex
@misc{watanabe2018espnet,
  title={ESPnet: End-to-End Speech Processing Toolkit},
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  year={2018},
  eprint={1804.00015},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
```
