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--- |
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tags: |
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- espnet |
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- audio |
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- codec |
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language: multilingual |
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datasets: |
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- amuse |
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license: cc-by-4.0 |
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--- |
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## ESPnet2 Codec model |
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### `espnet/dac_16k_music_single_survey` |
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This model was trained by ftshijt using amuse recipe in [espnet](https://github.com/espnet/espnet/). |
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### Demo: How to use in ESPnet2 |
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Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) |
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if you haven't done that already. |
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```bash |
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cd espnet |
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git checkout 9baec3a7b10b784cb721849e19caed19e8ac45bc |
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pip install -e . |
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cd egs2/amuse/codec1 |
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/dac_16k_music_single_survey |
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``` |
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## Codec config |
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<details><summary>expand</summary> |
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``` |
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config: conf/train_dac_large_v1.4_single.yaml |
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print_config: false |
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log_level: INFO |
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drop_last_iter: false |
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dry_run: false |
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iterator_type: chunk |
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valid_iterator_type: null |
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output_dir: exp_bench_16k/codec_dac_16k_music_single |
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ngpu: 1 |
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seed: 777 |
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num_workers: 1 |
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num_att_plot: 0 |
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dist_backend: nccl |
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dist_init_method: env:// |
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dist_world_size: 2 |
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dist_rank: 0 |
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local_rank: 0 |
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dist_master_addr: localhost |
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dist_master_port: 53969 |
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dist_launcher: null |
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multiprocessing_distributed: true |
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unused_parameters: true |
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sharded_ddp: false |
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use_deepspeed: false |
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deepspeed_config: null |
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cudnn_enabled: true |
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cudnn_benchmark: false |
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cudnn_deterministic: false |
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use_tf32: false |
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collect_stats: false |
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write_collected_feats: false |
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max_epoch: 360 |
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patience: null |
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val_scheduler_criterion: |
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- valid |
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- loss |
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early_stopping_criterion: |
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- valid |
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- loss |
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- min |
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best_model_criterion: |
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- - valid |
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- mel_loss |
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- min |
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- - train |
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- mel_loss |
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- min |
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- - train |
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- total_count |
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- max |
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keep_nbest_models: 5 |
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nbest_averaging_interval: 0 |
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grad_clip: -1 |
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grad_clip_type: 2.0 |
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grad_noise: false |
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accum_grad: 1 |
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no_forward_run: false |
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resume: true |
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train_dtype: float32 |
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use_amp: false |
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log_interval: 50 |
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use_matplotlib: true |
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use_tensorboard: true |
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create_graph_in_tensorboard: false |
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use_wandb: false |
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wandb_project: null |
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wandb_id: null |
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wandb_entity: null |
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wandb_name: null |
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wandb_model_log_interval: -1 |
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detect_anomaly: false |
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use_adapter: false |
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adapter: lora |
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save_strategy: all |
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adapter_conf: {} |
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pretrain_path: null |
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init_param: [] |
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ignore_init_mismatch: false |
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freeze_param: [] |
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num_iters_per_epoch: 5000 |
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batch_size: 64 |
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valid_batch_size: null |
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batch_bins: 1000000 |
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valid_batch_bins: null |
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category_sample_size: 10 |
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train_shape_file: |
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- exp_bench_16k/music_stats/train/audio_shape |
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valid_shape_file: |
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- exp_bench_16k/music_stats/valid/audio_shape |
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batch_type: unsorted |
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valid_batch_type: null |
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fold_length: |
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- 256000 |
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sort_in_batch: descending |
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shuffle_within_batch: false |
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sort_batch: descending |
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multiple_iterator: false |
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chunk_length: 32000 |
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chunk_shift_ratio: 0.5 |
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num_cache_chunks: 256 |
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chunk_excluded_key_prefixes: [] |
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chunk_default_fs: null |
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chunk_max_abs_length: null |
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chunk_discard_short_samples: true |
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train_data_path_and_name_and_type: |
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- - dump_bench_16k/raw/music_train_1k/wav.scp |
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- audio |
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- kaldi_ark |
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valid_data_path_and_name_and_type: |
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- - dump_bench_16k/raw/dev-small/wav.scp |
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- audio |
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- kaldi_ark |
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multi_task_dataset: false |
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allow_variable_data_keys: false |
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max_cache_size: 0.0 |
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max_cache_fd: 32 |
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allow_multi_rates: false |
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valid_max_cache_size: null |
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exclude_weight_decay: false |
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exclude_weight_decay_conf: {} |
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optim: adamw |
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optim_conf: |
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lr: 0.0002 |
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betas: |
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- 0.5 |
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- 0.9 |
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eps: 1.0e-09 |
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weight_decay: 0.0 |
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scheduler: exponentiallr |
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scheduler_conf: |
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gamma: 0.999875 |
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optim2: adamw |
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optim2_conf: |
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lr: 0.0002 |
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betas: |
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- 0.5 |
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- 0.9 |
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eps: 1.0e-09 |
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weight_decay: 0.0 |
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scheduler2: exponentiallr |
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scheduler2_conf: |
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gamma: 0.999875 |
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generator_first: true |
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skip_discriminator_prob: 0.0 |
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model_conf: {} |
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use_preprocessor: true |
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codec: dac |
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codec_conf: |
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sampling_rate: 16000 |
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generator_params: |
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hidden_dim: 512 |
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codebook_dim: 512 |
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encdec_channels: 1 |
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encdec_n_filters: 32 |
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encdec_n_residual_layers: 3 |
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encdec_ratios: |
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- 8 |
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- 5 |
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- 4 |
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- 2 |
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encdec_activation: Snake |
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encdec_norm: weight_norm |
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encdec_kernel_size: 7 |
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encdec_residual_kernel_size: 7 |
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encdec_last_kernel_size: 7 |
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encdec_dilation_base: 2 |
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encdec_causal: false |
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encdec_pad_mode: reflect |
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encdec_true_skip: false |
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encdec_compress: 2 |
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encdec_lstm: 2 |
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decoder_trim_right_ratio: 1.0 |
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decoder_final_activation: null |
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decoder_final_activation_params: null |
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quantizer_n_q: 1 |
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quantizer_bins: 1024 |
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quantizer_decay: 0.99 |
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quantizer_kmeans_init: true |
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quantizer_kmeans_iters: 50 |
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quantizer_threshold_ema_dead_code: 2 |
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quantizer_target_bandwidth: |
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- 0.5 |
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quantizer_dropout: true |
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sample_rate: 16000 |
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discriminator_params: |
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msmpmb_discriminator_params: |
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rates: [] |
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sample_rate: 24000 |
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fft_sizes: |
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- 2048 |
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- 1024 |
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- 512 |
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periods: |
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- 2 |
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- 3 |
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- 5 |
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- 7 |
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- 11 |
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period_discriminator_params: |
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in_channels: 1 |
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out_channels: 1 |
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kernel_sizes: |
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- 5 |
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- 3 |
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channels: 32 |
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downsample_scales: |
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- 3 |
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- 3 |
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- 3 |
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- 3 |
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- 1 |
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max_downsample_channels: 1024 |
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bias: true |
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nonlinear_activation: LeakyReLU |
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nonlinear_activation_params: |
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negative_slope: 0.1 |
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use_weight_norm: true |
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use_spectral_norm: false |
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band_discriminator_params: |
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hop_factor: 0.25 |
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sample_rate: 24000 |
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bands: |
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- - 0.0 |
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- 0.1 |
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- - 0.1 |
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- 0.25 |
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- - 0.25 |
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- 0.5 |
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- - 0.5 |
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- 0.75 |
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- - 0.75 |
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- 1.0 |
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channel: 32 |
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generator_adv_loss_params: |
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average_by_discriminators: false |
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loss_type: mse |
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discriminator_adv_loss_params: |
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average_by_discriminators: false |
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loss_type: mse |
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use_feat_match_loss: true |
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feat_match_loss_params: |
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average_by_discriminators: false |
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average_by_layers: false |
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include_final_outputs: true |
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use_mel_loss: true |
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mel_loss_params: |
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range_start: 6 |
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range_end: 11 |
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window: hann |
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n_mels: 80 |
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fmin: 0 |
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fmax: null |
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log_base: null |
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fs: 16000 |
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lambda_quantization: 0.25 |
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lambda_commit: 1.0 |
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lambda_reconstruct: 1.0 |
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lambda_adv: 1.0 |
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lambda_mel: 45.0 |
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lambda_feat_match: 2.0 |
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cache_generator_outputs: true |
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required: |
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- output_dir |
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version: '202402' |
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distributed: true |
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``` |
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</details> |
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### Citing ESPnet |
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```BibTex |
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@inproceedings{watanabe2018espnet, |
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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}, |
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title={{ESPnet}: End-to-End Speech Processing Toolkit}, |
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year={2018}, |
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booktitle={Proceedings of Interspeech}, |
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pages={2207--2211}, |
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doi={10.21437/Interspeech.2018-1456}, |
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456} |
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} |
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``` |
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or arXiv: |
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```bibtex |
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@misc{watanabe2018espnet, |
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title={ESPnet: End-to-End Speech Processing Toolkit}, |
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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}, |
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year={2018}, |
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eprint={1804.00015}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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