Merge pull request espnet#5840 from shimhz/spk_update_rats

Add RATS dataset for SV task

egs2/README.md

@@ -147,6 +147,7 @@ See: https://espnet.github.io/espnet/espnet2_tutorial.html#recipes-using-espnet2
 | primewords_chinese      | Primewords Chinese Corpus Set 1                                                                                                  | ASR                     | CMN                  | https://www.openslr.org/47/                                                                                  |              |
 | puebla_nahuatl          | Highland Puebla Nahuatl corpus (endangered language in central Mexico)                                                           | ASR/ST                  | HPN                  | https://www.openslr.org/92/                                                                                  |              |
 | qasr_tts                | TTS character based system using semi-supervised data selection                                                                  | TTS                     | ARA                  | https://arabicspeech.org/qasr_tts                                                                                  |              |
+| rats | RATS Speaker Identification | SPK | 5 languages | https://catalog.ldc.upenn.edu/LDC2021S08 |              |
 | reasonspeech            | ReazonSpeech: Japanese Corpus collected from TV Programs                                                                         | ASR                     | JPN                  | https://research.reazon.jp/projects/ReazonSpeech/                                                            |              |
 | reverb                  | REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge                                                       | ASR                     | ENG                  | https://reverb2014.dereverberation.com/                                                                      |              |
 | ru_open_stt             | Russian Open Speech To Text (STT/ASR) Dataset                                                                                    | ASR                     | RUS                  | https://github.com/snakers4/open_stt                                                                         |              |

egs2/rats/spk1/README.md

@@ -0,0 +1,19 @@
+# RESULTS
+
+Overall results
+| Model (conf name) | EER(%) | minDCF | Note | Huggingface |
+| [conf/train_SKA_wavlm_frozen.yaml](conf/train_SKA_wavlm_frozen.yaml) | 19.728 | 0.92968 | SKA-TDNN w/ Frozen WavLM | https://huggingface.co/espnet/rats_ska_wavlm_frozen |
+
+## Environments - conf/train_SKA_wavlm_frozen.yaml
+- python version: 3.9.19 (main, May  6 2024, 19:43:03)  [GCC 11.2.0]
+- espnet version: 202402
+- pytorch version: 1.13.1
+
+| | Mean | Std |
+|---|---|---|
+| Target | -1.0478 | 0.2006 |
+| Non-target | 0.1717 | 0.1717 |
+
+| Model name | EER(%) | minDCF |
+|---|---|---|
+| conf/train_SKA_wavlm_frozen | 19.728 | 0.92968 |

egs2/rats/spk1/cmd.sh

@@ -0,0 +1,110 @@
+# ====== About run.pl, queue.pl, slurm.pl, and ssh.pl ======
+# Usage: <cmd>.pl [options] JOB=1:<nj> <log> <command...>
+# e.g.
+#   run.pl --mem 4G JOB=1:10 echo.JOB.log echo JOB
+#
+# Options:
+#   --time <time>: Limit the maximum time to execute.
+#   --mem <mem>: Limit the maximum memory usage.
+#   -–max-jobs-run <njob>: Limit the number parallel jobs. This is ignored for non-array jobs.
+#   --num-threads <ngpu>: Specify the number of CPU core.
+#   --gpu <ngpu>: Specify the number of GPU devices.
+#   --config: Change the configuration file from default.
+#
+# "JOB=1:10" is used for "array jobs" and it can control the number of parallel jobs.
+# The left string of "=", i.e. "JOB", is replaced by <N>(Nth job) in the command and the log file name,
+# e.g. "echo JOB" is changed to "echo 3" for the 3rd job and "echo 8" for 8th job respectively.
+# Note that the number must start with a positive number, so you can't use "JOB=0:10" for example.
+#
+# run.pl, queue.pl, slurm.pl, and ssh.pl have unified interface, not depending on its backend.
+# These options are mapping to specific options for each backend and
+# it is configured by "conf/queue.conf" and "conf/slurm.conf" by default.
+# If jobs failed, your configuration might be wrong for your environment.
+#
+#
+# The official documentation for run.pl, queue.pl, slurm.pl, and ssh.pl:
+#   "Parallelization in Kaldi": http://kaldi-asr.org/doc/queue.html
+# =========================================================~
+
+
+# Select the backend used by run.sh from "local", "stdout", "sge", "slurm", or "ssh"
+cmd_backend='local'
+
+# Local machine, without any Job scheduling system
+if [ "${cmd_backend}" = local ]; then
+
+    # The other usage
+    export train_cmd="run.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="run.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="run.pl"
+
+# Local machine logging to stdout and log file, without any Job scheduling system
+elif [ "${cmd_backend}" = stdout ]; then
+
+    # The other usage
+    export train_cmd="stdout.pl"
+    # Used for "*_train.py": "--gpu" is appended optionally by run.sh
+    export cuda_cmd="stdout.pl"
+    # Used for "*_recog.py"
+    export decode_cmd="stdout.pl"
+
+
+# "qsub" (Sun Grid Engine, or derivation of it)
+elif [ "${cmd_backend}" = sge ]; then
+    # The default setting is written in conf/queue.conf.
+    # You must change "-q g.q" for the "queue" for your environment.
+    # To know the "queue" names, type "qhost -q"
+    # Note that to use "--gpu *", you have to setup "complex_value" for the system scheduler.
+
+    export train_cmd="queue.pl"
+    export cuda_cmd="queue.pl"
+    export decode_cmd="queue.pl"
+
+
+# "qsub" (Torque/PBS.)
+elif [ "${cmd_backend}" = pbs ]; then
+    # The default setting is written in conf/pbs.conf.
+
+    export train_cmd="pbs.pl"
+    export cuda_cmd="pbs.pl"
+    export decode_cmd="pbs.pl"
+
+
+# "sbatch" (Slurm)
+elif [ "${cmd_backend}" = slurm ]; then
+    # The default setting is written in conf/slurm.conf.
+    # You must change "-p cpu" and "-p gpu" for the "partition" for your environment.
+    # To know the "partion" names, type "sinfo".
+    # You can use "--gpu * " by default for slurm and it is interpreted as "--gres gpu:*"
+    # The devices are allocated exclusively using "${CUDA_VISIBLE_DEVICES}".
+
+    export train_cmd="slurm.pl"
+    export cuda_cmd="slurm.pl"
+    export decode_cmd="slurm.pl"
+
+elif [ "${cmd_backend}" = ssh ]; then
+    # You have to create ".queue/machines" to specify the host to execute jobs.
+    # e.g. .queue/machines
+    #   host1
+    #   host2
+    #   host3
+    # Assuming you can login them without any password, i.e. You have to set ssh keys.
+
+    export train_cmd="ssh.pl"
+    export cuda_cmd="ssh.pl"
+    export decode_cmd="ssh.pl"
+
+# This is an example of specifying several unique options in the JHU CLSP cluster setup.
+# Users can modify/add their own command options according to their cluster environments.
+elif [ "${cmd_backend}" = jhu ]; then
+
+    export train_cmd="queue.pl --mem 2G"
+    export cuda_cmd="queue-freegpu.pl --mem 2G --gpu 1 --config conf/queue.conf"
+    export decode_cmd="queue.pl --mem 4G"
+
+else
+    echo "$0: Error: Unknown cmd_backend=${cmd_backend}" 1>&2
+    return 1
+fi

egs2/rats/spk1/conf/pbs.conf

@@ -0,0 +1,11 @@
+# Default configuration
+command qsub -V -v PATH -S /bin/bash
+option name=* -N $0
+option mem=* -l mem=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -l ncpus=$0
+option num_threads=1  # Do not add anything to qsub_opts
+option num_nodes=* -l nodes=$0:ppn=1
+default gpu=0
+option gpu=0
+option gpu=* -l ngpus=$0

egs2/rats/spk1/conf/queue.conf

@@ -0,0 +1,12 @@
+# Default configuration
+command qsub -v PATH -cwd -S /bin/bash -j y -l arch=*64*
+option name=* -N $0
+option mem=* -l mem_free=$0,ram_free=$0
+option mem=0          # Do not add anything to qsub_opts
+option num_threads=* -pe smp $0
+option num_threads=1  # Do not add anything to qsub_opts
+option max_jobs_run=* -tc $0
+option num_nodes=* -pe mpi $0  # You must set this PE as allocation_rule=1
+default gpu=0
+option gpu=0
+option gpu=* -l gpu=$0 -q g.q

egs2/rats/spk1/conf/slurm.conf

@@ -0,0 +1,14 @@
+# Default configuration
+command sbatch --export=PATH
+option name=* --job-name $0
+option time=* --time $0
+option mem=* --mem-per-cpu $0
+option mem=0
+option num_threads=* --cpus-per-task $0
+option num_threads=1 --cpus-per-task 1
+option num_nodes=* --nodes $0
+default gpu=0
+option gpu=0 -p cpu
+option gpu=* -p gpu --gres=gpu:$0 -c $0  # Recommend allocating more CPU than, or equal to the number of GPU
+# note: the --max-jobs-run option is supported as a special case
+# by slurm.pl and you don't have to handle it in the config file.

egs2/rats/spk1/conf/train_RawNet3.yaml

@@ -0,0 +1,90 @@
+# RawNet3 reproduce recipe configuration.
+# Requires approx. 30GRAM per GPU when run with 2GPUs
+
+# Frontend
+frontend: asteroid_frontend
+frontend_conf:
+    sinc_stride: 16
+    sinc_kernel_size: 251
+    sinc_filters: 256
+    preemph_coef: 0.97
+    log_term: 0.000001
+
+# Encoder
+encoder: rawnet3
+encoder_conf:
+  model_scale: 8
+  ndim: 1024
+  output_size: 1536
+
+# Pooling
+pooling: chn_attn_stat
+
+# Projector
+projector: rawnet3
+projector_conf:
+  output_size: 192
+
+# Preprocessor
+preprocessor: spk
+preprocessor_conf:
+  target_duration: 3.0  # seconds
+  sample_rate: 16000
+  num_eval: 5
+  noise_apply_prob: 0.0
+  noise_info:
+  - [1.0, 'dump/raw/musan_speech.scp', [4, 7], [13, 20]]
+  - [1.0, 'dump/raw/musan_noise.scp', [1, 1], [0, 15]]
+  - [1.0, 'dump/raw/musan_music.scp', [1, 1], [5, 15]]
+  rir_apply_prob: 0.0
+
+# Model config
+model_conf:
+  extract_feats_in_collect_stats: false
+
+# Loss
+loss: aamsoftmax_sc_topk
+loss_conf:
+  margin: 0.3
+  scale: 30
+  K: 3
+  mp: 0.06
+  k_top: 5
+
+# Training related
+max_epoch: 50
+num_att_plot: 0
+num_workers: 8
+cudnn_deterministic: False
+cudnn_benchmark: True
+drop_last_iter: True
+iterator_type: category
+valid_iterator_type: sequence
+shuffle_within_batch: False
+log_interval: 10
+batch_size: 512
+valid_batch_size: 40
+use_amp: True
+keep_nbest_models: 3
+grad_clip: 9999
+best_model_criterion:
+- - valid
+  - eer
+  - min
+
+# Optimizer
+optim: adam
+optim_conf:
+  lr: 0.001
+  weight_decay: 0.00005
+  amsgrad: False
+
+# Scheduler
+scheduler: CosineAnnealingWarmupRestarts
+scheduler_conf:
+  first_cycle_steps: 5200 # equal to 50 epochs
+  cycle_mult: 1.0
+  max_lr: 0.001
+  min_lr: 0.000005
+  warmup_steps: 500
+  gamma: 0.75

egs2/rats/spk1/conf/train_SKA_wavlm_frozen.yaml

@@ -0,0 +1,96 @@
+# ECAPA-TDNN reproduce recipe configuration.
+
+# Frontend
+frontend: s3prl
+frontend_conf:
+    frontend_conf:
+        upstream: wavlm_large
+    download_dir: ./hub
+    multilayer_feature: True
+
+freeze_param: [
+  "frontend.upstream"
+]
+
+# Normalizer
+normalize: utterance_mvn
+normalize_conf:
+    norm_vars: false
+
+# Encoder
+encoder: ska_tdnn
+encoder_conf:
+  model_scale: 8
+  ndim: 1024
+  ska_dim: 128
+  output_size: 1536
+
+# Pooling
+pooling: chn_attn_stat
+
+# Projector
+projector: ska_tdnn
+projector_conf:
+  output_size: 192
+
+# Preprocessor
+preprocessor: spk
+preprocessor_conf:
+  target_duration: 3.0  # seconds
+  sample_rate: 16000
+  num_eval: 5
+  noise_apply_prob: 0.0
+  noise_info:
+  rir_apply_prob: 0.0
+
+# Model conf
+model_conf:
+  extract_feats_in_collect_stats: false
+
+# Loss
+loss: aamsoftmax_sc_topk
+loss_conf:
+  margin: 0.3
+  scale: 30
+  K: 3
+  mp: 0.06
+  k_top: 5
+
+# Training related
+max_epoch: 40
+num_att_plot: 0
+num_workers: 6
+cudnn_deterministic: False
+cudnn_benchmark: True
+drop_last_iter: True
+iterator_type: category
+valid_iterator_type: sequence
+shuffle_within_batch: False
+log_interval: 100
+batch_size: 64
+accum_grad: 8
+valid_batch_size: 5
+use_amp: True
+keep_nbest_models: 3
+grad_clip: 9999
+best_model_criterion:
+- - valid
+  - eer
+  - min
+
+# Optimizer
+optim: adam
+optim_conf:
+  lr: 0.001
+  weight_decay: 0.00005
+  amsgrad: False
+
+# Scheduler
+scheduler: CosineAnnealingWarmupRestarts
+scheduler_conf:
+  first_cycle_steps: 71280 # equal to 10 epochs
+  cycle_mult: 1.0
+  max_lr: 0.001
+  min_lr: 0.000005
+  warmup_steps: 1000
+  gamma: 0.75

egs2/rats/spk1/db.sh

@@ -0,0 +1 @@
+../../TEMPLATE/spk1/db.sh