ESPnet2 pretrained model, siddhana/slurp_entity_asr_train_asr_conformer_raw_en_word_valid.acc.ave_10best, fs=16k, lang=en
Creators: name: Siddhana
Publisher: name: Zenodo
Year: 2021
Subjects: ESPnet
deep-learning
python
pytorch
speech-recognition
speech-synthesis
speech-translation
machine-translation

description: This model was trained by siddhana using slurp_entity 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 pip install -e . cd egs2/slurp_entity_2/asr1 ./run.sh --skip_data_prep false --skip_train true --download_model siddhana/slurp_entity_2_asr_train_asr_conformer_raw_en_word_valid.acc.ave_10best</code> </pre> <strong>Results</strong> <pre><code> # RESULTS ## Environments - date: `Thu Oct 28 16:54:32 2021 -0400` - python version: `3.9.5 (default, Jun 4 2021, 12:28:51) [GCC 7.5.0]` - espnet version: `espnet 0.10.3a2` - pytorch version: `pytorch 1.8.1+cu102` - Git hash: `d7093719d98692774bb47d3c9470a1ca94d33866` - Commit date: `Thu Oct 28 16:54:32 2021 -0400` ## Using Conformer based encoder and Transformer based decoder with spectral augmentation and predicting transcript along with intent - ASR config: [conf/train_asr.yaml](conf/tuning/train_asr_conformer.yaml) - token_type: word - Entity classification code borrowed from SLURP [1] official repo - https://github.com/pswietojanski/slurp/tree/master/scripts/evaluation |dataset|Snt|Entity Classification (F1 Score)| |---|---|---| |inference_asr_model_valid.acc.ave_10best/test|13078|71.9| ### Intent Classification Results |dataset|Snt|Intent Classification (%)| |---|---|---| |inference_asr_model_valid.acc.ave_10best/test|13078|84.4| |inference_asr_model_valid.acc.ave_10best/valid|8690|85.4| ## Citation ``` @inproceedings{slurp, author = {Emanuele Bastianelli and Andrea Vanzo and Pawel Swietojanski and Verena Rieser}, title={{SLURP: A Spoken Language Understanding Resource Package}}, booktitle={{Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)}}, year={2020} } ```</code></pre> <strong>ASR config</strong> <pre><code>config: conf/tuning/train_asr_conformer.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/asr_train_asr_conformer_raw_en_word ngpu: 1 seed: 0 num_workers: 1 num_att_plot: 3 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: 40 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: 1 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: [] num_iters_per_epoch: null batch_size: 20 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - exp/asr_stats_raw_en_word/train/speech_shape - exp/asr_stats_raw_en_word/train/text_shape.word valid_shape_file: - exp/asr_stats_raw_en_word/valid/speech_shape - exp/asr_stats_raw_en_word/valid/text_shape.word batch_type: folded 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/wav.scp - speech - sound - - dump/raw/train/text - text - text valid_data_path_and_name_and_type: - - dump/raw/devel/wav.scp - speech - sound - - dump/raw/devel/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: 0.0002 scheduler: warmuplr scheduler_conf: warmup_steps: 25000 token_list: - - - ▁SEP - ▁FILL - s - ▁the - ▁to - a - ▁i - ▁me - ▁s - ▁a - i - e - ▁you - ▁what - er - u - ▁is - '''' - o - ing - p - ▁in - ▁p - y - ▁my - ▁please - d - m - ▁b - l - ▁c - date - n - ▁d - c - le - b - ▁m - ▁for - re - st - ▁on - t - en - h - 'on' - ar - person - ▁re - ▁f - ▁g - ▁of - an - ▁ - g - ▁today - ▁t - or - ▁it - ▁this - ▁h - r - f - at - ch - ce - place_name - ▁email - ▁do - es - ri - ▁e - ▁w - ic - in - ▁that - event_name - ▁play - ▁and - al - ▁n - ▁can - email_query - ve - ▁new - day - it - ate - ▁from - ▁have - k - time - ▁am - media_type - email_sendemail - ent - ▁olly - qa_factoid - v - et - ck - ▁any - calendar_set - ly - se - th - ▁how - ▁meeting - ed - ▁tell - ▁st - x - ur - ▁at - ro - nd - ▁list - ou - w - ▁u - ▁not - ▁about - ▁an - ▁o - general_negate - ut - ▁time - ▁be - ▁ch - ▁are - social_post - business_name - ty - la - play_music - ot - general_quirky - ▁l - ▁sh - ▁tweet - om - ▁week - um - ▁one - ter - ▁he - ▁up - ▁com - general_praise - weather_query - ▁next - ▁th - ▁check - calendar_query - ▁last - ▁ro - ad - is - ▁with - ay - ▁send - pe - ▁pm - ▁tomorrow - ▁j - un - ▁train - general_explain - ▁v - one - ▁r - ra - news_query - ation - ▁emails - us - if - ct - ▁co - ▁add - ▁will - ▁se - nt - ▁was - ine - ▁de - ▁set - ▁ex - ▁would - ir - ow - ber - general_repeat - ight - ook - ▁again - ▁song - currency_name - ll - ▁go - ▁ha - relation - te - ion - and - ▁y - ▁ye - general_affirm - general_confirm - ery - ▁po - ff - ▁we - ▁turn - ▁did - ▁mar - ▁alarm - ▁like - datetime_query - ers - ▁all - ▁remind - ▁so - qa_definition - ▁calendar - end - ▁said - ci - ▁off - ▁john - ss - ▁day - pla - ume - ▁get - pp - ail - z - ry - am - ▁need - as - ▁thank - ▁wh - ▁want - ▁right - ▁jo - ▁facebook - ▁k - ge - ld - ▁fri - ▁two - general_dontcare - ▁news - ol - oo - ant - ▁five - ▁event - ake - definition_word - transport_type - ▁your - vi - op - ▁weather - ome - ▁app - ▁lo - de - ▁music - weather_descriptor - ak - ke - ▁there - ▁si - ▁lights - ▁now - ▁mo - calendar_remove - our - ▁dollar - food_type - me - ▁more - ▁no - ▁birthday - orrect - ▁rep - ▁show - play_radio - ▁mon - ▁does - ood - li - ag - ▁sto - ▁contact - cket - email_querycontact - ▁ev - ▁could - ▁just - ange - out - ame - . - ▁ja - ▁confirm - qa_currency - ▁man - ▁some - ▁late - ▁think - timeofday - ▁bo - qa_stock - ong - ▁start - ▁work - ▁ten - int - ▁command - all - ▁make - ▁la - j - ▁answ - ▁hour - ▁cle - ah - ▁find - ▁service - ▁fa - qu - general_commandstop - ai - ▁when - ard - ▁te - ▁by - social_query - ul - ▁tw - id - ▁seven - ▁where - ▁much - art - ▁appointment - ver - artist_name - el - device_type - ▁know - ▁three - ▁events - ▁tr - ▁li - ork - red - ect - ▁let - ▁respon - ▁par - zz - ▁give - ▁twenty - ac - ▁morning - ▁ti - est - ▁curre - play_podcasts - ▁radio - cooking_recipe - transport_query - ▁con - gh - ▁le - lists_query - ▁rem - recommendation_events - house_place - alarm_set - play_audiobook - ist - ase - music_genre - ive - ast - ort - player_setting - lly - news_topic - list_name - ▁playlist - ▁ne - business_type - personal_info - ind - ust - di - ress - recommendation_locations - lists_createoradd - iot_hue_lightoff - lists_remove - ord - ▁light - ere - alarm_query - audio_volume_mute - music_query - ▁audio - rain - ▁date - ▁order - audio_volume_up - ▁ar - ▁podcast - transport_ticket - mail - iot_hue_lightchange - iot_coffee - radio_name - ill - ▁ri - '@' - takeaway_query - song_name - takeaway_order - ▁ra - email_addcontact - play_game - book - transport_traffic - ▁house - music_likeness - her - transport_taxi - iot_hue_lightdim - ment - ght - fo - order_type - color_type - '1' - ven - ould - general_joke - ess - ain - qa_maths - ▁place - ▁twe - cast - iot_cleaning - ▁che - ▁cont - orn - ith - audiobook_name - email_address - game_name - ▁cal - general_frequency - ▁tom - ▁food - act - iot_hue_lightup - '2' - alarm_remove - podcast_descriptor - ▁definition - audio_volume_down - ▁media - email_folder - dia - meal_type - ▁mus - recommendation_movies - ▁ad - ree - pt - now - playlist_name - ▁person - change_amount - ▁pla - escri - datetime_convert - podcast_name - ▁ab - time_zone - ▁def - ting - iot_wemo_on - music_settings - iot_wemo_off - orre - cy - ank - music_descriptor - lar - app_name - row - joke_type - set - xt - of - ition - ▁meet - ink - ▁confir - transport_agency - general_greet - ▁business - ▁art - ▁ag - urn - escript - rom - ▁rel - ▁au - ▁currency - audio_volume_other - iot_hue_lighton - ▁artist - ▁bus - '?' - cooking_type - movie_name - coffee_type - ingredient - music_dislikeness - ather - sp - q - ▁ser - esc - ▁bir - ▁cur - name - ▁tran - ▁hou - ek - uch - ▁conf - ▁face - '9' - ▁birth - I - sw - transport_descriptor - ▁comm - lease - transport_name - aid - movie_type - ▁device - alarm_type - audiobook_author - '5' - drink_type - ▁joh - ▁defin - word - ▁curren - order - iness - W - cooking_query - sport_type - ▁relation - oint - H - '8' - '0' - ▁dol - vice - ▁pers - '&amp;' - T - ▁appoint - A - '7' - '3' - '-' - game_type - ▁pod - _ - list - music_album - dio - ▁transport - qa_query - C - O - U - query_detail - spon - init: null input_size: null ctc_conf: dropout_rate: 0.0 ctc_type: builtin reduce: true ignore_nan_grad: true model_conf: ctc_weight: 0.3 lsm_weight: 0.1 length_normalized_loss: false extract_feats_in_collect_stats: false use_preprocessor: true token_type: word bpemodel: null non_linguistic_symbols: null cleaner: null g2p: null speech_volume_normalize: null rir_scp: null rir_apply_prob: 1.0 noise_scp: null noise_apply_prob: 1.0 noise_db_range: '13_15' frontend: default frontend_conf: fs: 16k specaug: specaug specaug_conf: apply_time_warp: true time_warp_window: 5 time_warp_mode: bicubic apply_freq_mask: true freq_mask_width_range: - 0 - 30 num_freq_mask: 2 apply_time_mask: true time_mask_width_range: - 0 - 40 num_time_mask: 2 normalize: utterance_mvn normalize_conf: {} preencoder: null preencoder_conf: {} encoder: conformer encoder_conf: output_size: 512 attention_heads: 8 linear_units: 2048 num_blocks: 12 dropout_rate: 0.1 positional_dropout_rate: 0.1 attention_dropout_rate: 0.1 input_layer: conv2d normalize_before: true macaron_style: true pos_enc_layer_type: rel_pos selfattention_layer_type: rel_selfattn activation_type: swish use_cnn_module: true cnn_module_kernel: 31 postencoder: null postencoder_conf: {} decoder: transformer decoder_conf: attention_heads: 8 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 required: - output_dir - token_list version: 0.10.3a2 distributed: false</code></pre> <strong>LM config</strong> <pre><code>NONE</code></pre>