Model reference · open weights
simpleoier_librispeech_asr_train_asr_conformer7_wavlm_large_raw_en_bpe5000_sp is an open-weight audio or speech model from espnet. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | espnet |
|---|---|
| Type | Audio & music |
| Task | Speech→text |
| Runs with | espnet |
| Released | 2022-03-02 |
| Popularity | 2k downloads / month |
| Licence | Open weights |
About
espnet/simpleoier_librispeech_asr_train_asr_conformer7_wavlm_large_raw_en_bpe5000_spThis model was trained by simpleoier using librispeech recipe in espnet.
cd espnet
git checkout b0ff60946ada6753af79423a2e6063984bec2926
pip install -e .
cd egs2/librispeech/asr1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/simpleoier_librispeech_asr_train_asr_conformer7_wavlm_large_raw_en_bpe5000_sp
Tue Jan 4 20:52:48 EST 20223.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]espnet 0.10.5a1pytorch 1.8.1| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_clean | 2703 | 54402 | 98.4 | 1.4 | 0.1 | 0.2 | 1.7 | 23.1 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_other | 2864 | 50948 | 96.7 | 3.0 | 0.3 | 0.3 | 3.6 | 35.5 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_clean | 2620 | 52576 | 98.4 | 1.5 | 0.1 | 0.2 | 1.8 | 23.7 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_other | 2939 | 52343 | 96.7 | 3.0 | 0.3 | 0.4 | 3.7 | 37.9 |
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_clean | 2703 | 288456 | 99.7 | 0.2 | 0.2 | 0.2 | 0.5 | 23.1 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_other | 2864 | 265951 | 98.9 | 0.6 | 0.4 | 0.4 | 1.5 | 35.5 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_clean | 2620 | 281530 | 99.6 | 0.2 | 0.2 | 0.2 | 0.6 | 23.7 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_other | 2939 | 272758 | 99.1 | 0.5 | 0.4 | 0.4 | 1.3 | 37.9 |
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_clean | 2703 | 68010 | 98.2 | 1.4 | 0.4 | 0.3 | 2.1 | 23.1 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_other | 2864 | 63110 | 96.0 | 3.1 | 0.9 | 0.9 | 4.9 | 35.5 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_clean | 2620 | 65818 | 98.1 | 1.4 | 0.5 | 0.4 | 2.3 | 23.7 |
| decode_asr_lm_lm_train_lm_transformer2_en_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/test_other | 2939 | 65101 | 96.1 | 2.9 | 1.0 | 0.8 | 4.7 | 37.9 |
config: conf/tuning/train_asr_conformer7_wavlm_large.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_asr_conformer7_wavlm_large_raw_en_bpe5000_sp
ngpu: 1
seed: 0
num_workers: 1
num_att_plot: 3
num_targets: 1
dist_backend: nccl
dist_init_method: env://
dist_world_size: 2
dist_rank: 0
local_rank: 0
dist_master_addr: localhost
dist_master_port: 45342
dist_launcher: null
multiprocessing_distributed: true
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: 3
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_tensorboard: true
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:
- frontend.upstream
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 40000000
valid_batch_bins: null
train_shape_file:
- exp/asr_stats_raw_en_bpe5000_sp/train/speech_shape
- exp/asr_stats_raw_en_bpe5000_sp/train/text_shape.bpe
valid_shape_file:
- exp/asr_stats_raw_en_bpe5000_sp/valid/speech_shape
- exp/asr_stats_raw_en_bpe5000_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
- kaldi_ark
- - dump/raw/train_960_sp/text
- text
- text
valid_data_path_and_name_and_type:
- - dump/raw/dev/wav.scp
- speech
- kaldi_ark
- - dump/raw/dev/text
- text
- text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
lr: 0.0025
scheduler: warmuplr
scheduler_conf:
warmup_steps: 40000
token_list:
-
-
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- ▁WOULD
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- ▁WILL
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- ▁ABOUT
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- ▁MFrom the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys simpleoier-librispeech-asr-train-asr-conformer7-wavlm-large-raw-en-bpe5000-sp for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (simpleoier-librispeech-asr-train-asr-conformer7-wavlm-large-raw-en-bpe5000-sp below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="simpleoier-librispeech-asr-train-asr-conformer7-wavlm-large-raw-en-bpe5000-sp" -F file=@audio.mp3
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.