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This model was trained by Shinji Watanabe using spgispeech 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 ddd205f05e4a323a0aeb5cae81604a7bb5abfa45 pip install -e . cd egs2/spgispeech/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model Shinji Watanabe/spgispeech_asr_train_asr_conformer6_n_fft512_hop_length256_raw_en_unnorm_bpe5000_valid.acc.ave Results # RESULTS ## Environments - date: `Sun Feb 28 07:20:31 EST 2021` - python version: `3.8.5 (default, Sep 4 2020, 07:30:14) [GCC 7.3.0]` - espnet version: `espnet 0.9.7` - pytorch version: `pytorch 1.7.1` - Git hash: `3572c4ecd74a9b1c77c639fce40e9318d254c5a6` - Commit date: `Thu Feb 25 18:52:24 2021 -0500` ## asr_train_asr_conformer6_n_fft512_hop_length256_raw_en_unnorm_bpe5000 ### WER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_4k_unnorm|4000|95631|94.9|4.5|0.6|0.5|5.5|61.0| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/val_unnorm|39341|948632|94.9|4.5|0.6|0.5|5.5|61.4| ### CER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_4k_unnorm|4000|554413|98.8|0.6|0.6|0.4|1.6|61.0| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/val_unnorm|39341|5502566|98.8|0.6|0.6|0.5|1.6|61.4| ### TER |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |---|---|---|---|---|---|---|---|---| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/dev_4k_unnorm|4000|117813|95.4|2.7|1.9|1.1|5.7|61.0| |decode_asr_lm_lm_train_lm_en_unnorm_bpe5000_valid.loss.ave_asr_model_valid.acc.ave/val_unnorm|39341|1169320|95.5|2.7|1.8|1.2|5.7|61.4| ASR config config: conf/tuning/train_asr_conformer6_n_fft512_hop_length256.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp_unnorm/asr_train_asr_conformer6_n_fft512_hop_length256_raw_en_unnorm_bpe5000 ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 4 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 59122 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 grad_clip: 5.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 4 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 pretrain_path: null init_param: [] freeze_param: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 35000000 valid_batch_bins: null train_shape_file: - exp_unnorm/asr_stats_raw_en_unnorm_bpe5000/train/speech_shape - exp_unnorm/asr_stats_raw_en_unnorm_bpe5000/train/text_shape.bpe valid_shape_file: - exp_unnorm/asr_stats_raw_en_unnorm_bpe5000/valid/speech_shape - exp_unnorm/asr_stats_raw_en_unnorm_bpe5000/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_unnorm/raw/train_nodev_unnorm/wav.scp - speech - sound - - dump_unnorm/raw/train_nodev_unnorm/text - text - text valid_data_path_and_name_and_type: - - dump_unnorm/raw/dev_4k_unnorm/wav.scp - speech - sound - - dump_unnorm/raw/dev_4k_unnorm/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: 0.0015 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 token_list: - - - ▁the - . - ',' - ▁to - ▁of - ▁and - ▁we - s - ▁in - ▁that - ▁a - '''' - ▁our - ▁is - ▁I - ▁on - ▁for - ▁you - ▁are - ▁have - ▁as - ▁with - ▁it - ▁be - ▁this - ▁We - re - ▁And - ▁will - '-' - t - ▁year - ▁quarter - ▁at - ing - ▁So - ▁more - ▁from - ▁business - ▁think - ▁not - ▁what - ▁some - d - ve - ▁us - ▁by - ▁about - ed - ▁there - ▁can - ▁growth - ▁new - ▁was - ▁which - ▁or - ▁do - ▁very - ▁an - '?' - ▁market - ▁continue - ▁but - ▁also - ▁would - ▁see - ▁going - ▁The - ▁-- - ▁they - ▁all - ▁been - ▁just - ▁has - ▁these - ▁so - ▁well - ▁over - ▁those - ▁now - ll - ▁time - ly - n - ▁out - ▁where - ▁into - ▁customers - ▁like - ▁first - ▁results - m - ▁But - ▁other - ▁really - ▁how - ▁if - ▁up - ▁their - ▁expect - ▁forward - ▁company - ▁than - ▁last - ▁were - ▁look - ▁your - ▁through - ▁get - ▁any - ▁call - ▁one - ▁because - ▁strong - ▁In - ▁had - ▁believe - ▁sales - ▁when - ▁good - ▁second - ▁This - ▁As - ▁revenue - ▁then - er - ▁lot - ▁make - ▁performance - ▁product - ▁cost - ▁much - y - ▁financial - ▁capital - ▁value - ▁Our - ▁could - ▁years - ▁right - ▁impact - ▁terms - ▁want - ▁future - ▁don - ▁both - ▁It - ▁them - ▁today - ▁work - ▁little - ▁back - ▁customer - ▁next - ▁bit - ▁increase - al - ▁end - ▁take - ▁products - ▁number - ▁kind - ▁higher - ▁opportunities - ▁half - ▁able - ▁way - ▁markets - ▁may - ▁know - ▁significant - ▁operating - ▁better - ▁go - ▁focus - ▁say - ▁cash - ▁2 - ▁part - ▁things - ▁still - ▁point - ▁provide - ▁most - ▁statements - ▁lower - ▁should - ▁team - ▁being - in - c - ▁need - 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ur - ▁potential - ▁services - ▁before - ▁large - ▁remain - ▁businesses - ▁pricing - ▁months - ▁These - ▁side - ▁making - ▁Q - ▁F - ▁done - ▁put - ▁something - ▁ability - ▁program - ▁interest - ▁experience - ▁strategic - ▁already - ▁platform - ▁sure - ▁production - ▁based - ▁use - ▁best - ▁feel - ▁such - ▁information - ▁segment - ▁acquisition - ▁mentioned - ▁period - ▁Now - ▁talk - ▁model - ▁maybe - ▁expectations - ▁early - ▁several - ▁You - ▁operations - ▁given - ▁deliver - ▁s - ▁base - ▁order - ▁assets - ▁pleased - term - ▁rates - ▁my - ▁changes - ▁tax - ▁place - ▁build - C - es - ▁benefit - ▁each - ▁couple - an - ▁growing - ▁improvement - ▁including - ▁under - ▁projects - ▁certain - ▁related - ▁flow - ▁initiatives - ▁addition - ▁fact - b - ion - a - ▁commercial - ▁companies - ▁activity - ▁driven - ▁areas - ers - ▁getting - ▁existing - ▁mix - ▁brand - ▁term - ▁margins - ▁volume - ▁levels - ▁pretty - ▁thing - ▁mean - ▁release - ic - ▁continues - ▁income - ▁course - ▁capacity - ▁big - P - it - ▁factors - ▁might - l - ▁competitive - ri - ▁clients - ▁probably - ▁net - ▁project - ▁always - ▁With - ▁does - en - ▁There - E - ▁risk - ▁B - ▁review - ▁every - ▁leverage - ▁Thank - able - ▁marketing - ▁amount - ▁off - ▁quite - ▁quarters - ▁saw - ▁update - ▁its - ▁P - ▁less - ment - ▁prices - ▁offset - ▁why - ▁view - ▁supply - ▁available - ▁world - ▁building - ▁after - ▁credit - ▁E - ▁having - ro - I - ▁recent - ▁de - ▁top - ▁success - ▁real - ▁between - ▁set - ▁prior - ▁efforts - ▁core - ▁global - ▁let - ▁digital - ▁quality - k - ▁Or - ▁conference - se - ▁area - ▁operational - ▁earlier - il - ▁T - ▁shareholders - ▁return - ra - ▁far - ▁system - ▁understand - ▁low - ▁range - ▁pipeline - ▁trying - ▁actual - ▁contract - ▁expenses - ▁primarily - ▁continuing - ▁another - ▁structure - ▁While - ▁certainly - ▁whether - ▁e - ▁solutions - ▁approach - ▁day - f - ▁own - ▁inventory - ▁questions - ▁outlook - ▁ahead - ▁For - to - ate - ▁taking - ▁improved - ▁presentation - ul - ▁expense - R - A - T - el - ▁thank - ▁non - ▁If - ▁major - ▁retail - ▁confident - ▁profitability - ch - ▁fiscal - ▁capabilities - ▁create - ▁timing - ▁group - ▁add - ▁expand - ▁un - ▁p - ▁materially - li - ▁clear - ▁risks - M - ▁total - ent - ▁b - ▁increasing - ▁expansion - O - ▁4 - ▁ago - ▁On - ▁consumer - ▁specific - ▁distribution - ▁D - ▁solid - ▁obviously - ▁excited - ▁hard - ▁space - ▁driving - ▁moving - D - ▁benefits - ▁What - ▁f - ▁invest - ▁talked - ▁differ - ▁acquisitions - ▁China - ▁revenues - ▁partners - ▁strength - ▁plans - ▁Yes - ▁sheet - ▁bring - la - ▁begin - ▁tell - ▁perspective - ▁keep - ▁particularly - at - th - ▁small - ▁increases - up - ▁1 - ▁5 - ▁debt - i - ▁They - ▁sense - ▁stores - ▁transaction - ▁U - ▁close - ▁versus - ▁asset - ▁R - ▁compared - ▁per - ▁improving - ▁network - ▁measures - '1' - ▁longer - ▁programs - ive - ▁patients - ▁run - ▁consistent - ▁open - ▁average - ▁significantly - as - L - ▁trends - ▁beginning - ▁control - ▁numbers - ▁scale - ▁needs - ▁care - ▁G - ▁currently - ry - ▁since - ▁conditions - ▁trend - ▁decline - ▁organization - ▁c - et - ▁innovation - ▁detail - ▁pay - ▁difficult - ▁include - ▁advantage - ▁profit - ▁N - ▁deal - ▁points - ▁execution - ▁anything - ▁towards - ▁volumes - ▁cause - ▁together - ▁access - ▁material - ▁larger - ▁However - ▁spend - ▁starting - ▁efficiency - ▁uncertainties - ▁reduce - ▁example - ▁remains - ▁record - ▁At - ▁throughout - ▁later - ▁comments - ▁ongoing - ▁fully - ▁gas - ▁store - ▁greater - ▁organic - ▁yet - ▁events - ▁along - ▁M - ▁successful - ol - ▁short - ▁2017 - ▁To - ▁announced - ▁con - est - h - ter - ▁morning - ▁note - ▁sell - ▁discuss - ▁find - ▁Europe - ne - te - ▁started - ▁brands - ▁allow - ▁returns - ▁transition - ▁case - ▁particular - ▁track - ▁front - ▁achieve - ▁talking - ▁become - ▁manage - ▁similar - ▁decision - ▁oil - im - ▁international - ▁infrastructure - ▁health - ▁momentum - ▁providing - ized - ▁Okay - ▁recently - ies - ▁completed - ▁job - ▁press - ▁direct - ▁economic - ▁Re - ▁book - ▁shift - 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python, speech-synthesis, pytorch, machine-translation, ESPnet, speech-translation, deep-learning, speech-recognition
python, speech-synthesis, pytorch, machine-translation, ESPnet, speech-translation, deep-learning, speech-recognition
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