| --- |
| tags: |
| - espnet |
| - audio |
| - universa |
| language: multilingual |
| datasets: |
| - universa_unite |
| license: cc-by-4.0 |
| --- |
| |
| ## ESPnet2 universa model |
|
|
| ### `espnet/arecho_base_v0.1-large-decoder` |
|
|
| This model was trained by ftshijt using universa_unite 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 0b68ffd26362f4b50e7c73942c5bbdbc0a220bd4 |
| pip install -e . |
| cd egs2/universa_unite/uni_versa1 |
| ./run.sh --skip_data_prep false --skip_train true --download_model espnet/arecho_base_v0.1-large-decoder |
| ``` |
| |
| |
| |
| ## universa config |
| |
| <details><summary>expand</summary> |
| |
| ``` |
| config: conf/train_aruniversa_wavlm_large.yaml |
| print_config: false |
| log_level: INFO |
| drop_last_iter: false |
| dry_run: false |
| iterator_type: sequence |
| valid_iterator_type: null |
| output_dir: exp/universa_universa_ar_overall_base_token_wavlm_large |
| ngpu: 1 |
| seed: 777 |
| num_workers: 1 |
| num_att_plot: 0 |
| 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 |
| use_deepspeed: false |
| deepspeed_config: null |
| gradient_as_bucket_view: true |
| ddp_comm_hook: null |
| cudnn_enabled: true |
| cudnn_benchmark: false |
| cudnn_deterministic: false |
| use_tf32: false |
| 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: |
| - - train |
| - loss |
| - min |
| - - valid |
| - loss |
| - min |
| - - train |
| - acc |
| - max |
| - - valid |
| - acc |
| - max |
| keep_nbest_models: 1 |
| nbest_averaging_interval: 0 |
| grad_clip: -1 |
| grad_clip_type: 2.0 |
| grad_noise: false |
| accum_grad: 2 |
| no_forward_run: false |
| resume: true |
| train_dtype: float32 |
| use_amp: false |
| log_interval: 50 |
| 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 |
| use_adapter: false |
| adapter: lora |
| save_strategy: all |
| adapter_conf: {} |
| pretrain_path: null |
| init_param: [] |
| ignore_init_mismatch: false |
| freeze_param: |
| - frontend.upstream |
| num_iters_per_epoch: null |
| batch_size: 16 |
| valid_batch_size: null |
| batch_bins: 1000000 |
| valid_batch_bins: null |
| category_sample_size: 10 |
| train_shape_file: |
| - exp/universa_stats_overall_base/train/audio_shape |
| - exp/universa_stats_overall_base/train/ref_audio_shape |
| valid_shape_file: |
| - exp/universa_stats_overall_base/valid/audio_shape |
| - exp/universa_stats_overall_base/valid/ref_audio_shape |
| batch_type: sorted |
| valid_batch_type: null |
| fold_length: |
| - 256000 |
| sort_in_batch: descending |
| shuffle_within_batch: false |
| sort_batch: descending |
| multiple_iterator: false |
| chunk_length: 500 |
| chunk_shift_ratio: 0.5 |
| num_cache_chunks: 1024 |
| chunk_excluded_key_prefixes: [] |
| chunk_default_fs: null |
| chunk_max_abs_length: null |
| chunk_discard_short_samples: true |
| train_data_path_and_name_and_type: |
| - - dump/raw/overall_base/wav.scp |
| - audio |
| - kaldi_ark |
| - - dump/raw/overall_base/metric.scp |
| - metrics |
| - metric |
| - - dump/raw/overall_base/ref_wav.scp |
| - ref_audio |
| - kaldi_ark |
| valid_data_path_and_name_and_type: |
| - - dump/raw/overall_dev/wav.scp |
| - audio |
| - kaldi_ark |
| - - dump/raw/overall_dev/metric.scp |
| - metrics |
| - metric |
| - - dump/raw/overall_dev/ref_wav.scp |
| - ref_audio |
| - kaldi_ark |
| multi_task_dataset: false |
| allow_variable_data_keys: false |
| max_cache_size: 0.0 |
| max_cache_fd: 32 |
| allow_multi_rates: false |
| valid_max_cache_size: null |
| exclude_weight_decay: false |
| exclude_weight_decay_conf: {} |
| optim: adamw |
| optim_conf: |
| lr: 0.001 |
| scheduler: warmuplr |
| scheduler_conf: |
| warmup_steps: 25000 |
| metric2id: dump/raw/overall_base/metric2id |
| metric2type: dump/raw/overall_base/metric2type |
| metric_pad_value: -100 |
| token_list: null |
| metric_token_info: data/token_list/metric_500_percentile_overall_base_w-numerical/tokens.json |
| metric_token_pad_value: 0 |
| tokenize_numerical_metric: true |
| init: null |
| model_conf: {} |
| use_ref_audio: true |
| use_ref_text: false |
| use_preprocessor: true |
| token_type: bpe |
| bpemodel: null |
| non_linguistic_symbols: null |
| cleaner: null |
| g2p: null |
| sequential_metric: true |
| randomize_sequential_metric: true |
| frontend: s3prl |
| frontend_conf: |
| frontend_conf: |
| upstream: wavlm_large |
| download_dir: ./hub |
| multilayer_feature: true |
| universa: ar_universa |
| universa_conf: |
| embedding_dim: 512 |
| audio_encoder_type: transformer |
| audio_encoder_params: |
| num_blocks: 4 |
| attention_heads: 4 |
| linear_units: 1024 |
| dropout_rate: 0.1 |
| positional_dropout_rate: 0.1 |
| attention_dropout_rate: 0.1 |
| input_layer: conv2d |
| normalize_before: true |
| concat_after: false |
| positionwise_layer_type: linear |
| positionwise_conv_kernel_size: 1 |
| layer_drop_rate: 0.1 |
| qk_norm: false |
| use_flash_attn: false |
| cross_attention_type: multihead |
| cross_attention_params: |
| n_head: 2 |
| dropout_rate: 0.1 |
| metric_decoder_params: |
| num_blocks: 12 |
| attention_heads: 8 |
| linear_units: 2048 |
| dropout_rate: 0.1 |
| positional_dropout_rate: 0.1 |
| src_attention_dropout_rate: 0.1 |
| self_attention_dropout_rate: 0.1 |
| input_layer: embed |
| normalize_before: true |
| concat_after: false |
| layer_drop_rate: 0.1 |
| qk_norm: false |
| use_flash_attn: false |
| use_rope: true |
| lsm_weight: 0.1 |
| sym_sos: <sos> |
| sym_eos: <eos> |
| required: |
| - output_dir |
| - metric2id |
| version: '202503' |
| 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} |
| } |
| ``` |
|
|
