ESPnet2 DIAR model

`YushiUeda/test`

This model was trained by Yushi Ueda using mini_librispeech recipe in espnet.

Demo: How to use in ESPnet2

cd espnet
git checkout 4dfa2be4331d3d68f124aa5fd81f63217a7278a4
pip install -e .
cd egs2/mini_librispeech/diar1
./run.sh --skip_data_prep false --skip_train true --download_model YushiUeda/test

RESULTS

Environments

date: Wed Aug 25 23:29:07 EDT 2021
python version: 3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]
espnet version: espnet 0.10.2a1
pytorch version: pytorch 1.9.0+cu102
Git hash: 19bcd34f9395e01e54a97c4db5ecbcedb429dd92
- Commit date: Tue Aug 24 19:50:44 2021 -0400

`diar_train_diar_raw_max_epoch20`

DER

dev_clean_2_ns2_beta2_500

threshold_median_collar	DER
result_th0.3_med1_collar0.0	32.42
result_th0.3_med11_collar0.0	32.03
result_th0.4_med1_collar0.0	30.96
result_th0.4_med11_collar0.0	30.26
result_th0.5_med1_collar0.0	30.35
result_th0.5_med11_collar0.0	29.37
result_th0.6_med1_collar0.0	30.77
result_th0.6_med11_collar0.0	29.52
result_th0.7_med1_collar0.0	32.60
result_th0.7_med11_collar0.0	31.03

DIAR config

expand

config: conf/train_diar.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: chunk
output_dir: exp/diar_train_diar_raw_max_epoch20
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: 20
patience: 3
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 3
grad_clip: 5
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: 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: 16
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/diar_stats_8k/train/speech_shape
- exp/diar_stats_8k/train/spk_labels_shape
valid_shape_file:
- exp/diar_stats_8k/valid/speech_shape
- exp/diar_stats_8k/valid/spk_labels_shape
batch_type: folded
valid_batch_type: null
fold_length:
- 80000
- 800
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 200000
chunk_shift_ratio: 0.5
num_cache_chunks: 64
train_data_path_and_name_and_type:
-   - dump/raw/simu/data/train_clean_5_ns2_beta2_500/wav.scp
    - speech
    - sound
-   - dump/raw/simu/data/train_clean_5_ns2_beta2_500/espnet_rttm
    - spk_labels
    - rttm
valid_data_path_and_name_and_type:
-   - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/wav.scp
    - speech
    - sound
-   - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/espnet_rttm
    - spk_labels
    - rttm
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 0.01
scheduler: noamlr
scheduler_conf:
    warmup_steps: 1000
num_spk: 2
init: xavier_uniform
input_size: null
model_conf:
    loss_type: pit
use_preprocessor: true
frontend: default
frontend_conf:
    fs: 8k
    hop_length: 128
normalize: global_mvn
normalize_conf:
    stats_file: exp/diar_stats_8k/train/feats_stats.npz
encoder: transformer
encoder_conf:
    input_layer: linear
    num_blocks: 2
    linear_units: 512
    dropout_rate: 0.1
    output_size: 256
    attention_heads: 4
    attention_dropout_rate: 0.0
decoder: linear
decoder_conf: {}
label_aggregator: label_aggregator
label_aggregator_conf: {}
required:
- output_dir
version: 0.10.2a1
distributed: false