Comments (5)
I added the following to augmentor, and used the following snippet from online augmentation tutorial
rir_data_path = f'{data_dir}/dataset'
!python {NEMO_ROOT}/scripts/dataset_processing/get_openslr_rir_data.py --data_root {rir_data_path}
rir_manifest_path = os.path.join(rir_data_path, 'processed', 'rir.json')
!head -n 3 {rir_manifest_path}
Then to use the augmentation I applied the following
audio_augmentations = dict(
speed = dict(
sr=16000,
prob=0.3,
resample_type='kaiser_fast',
min_speed_rate=0.95,
max_speed_rate=1.05,
),
noise = dict(
manifest_path=rir_manifest_path,
prob=0.5,
min_snr_db=0,
max_snr_db=15,
),
)
finetune_config.model.train_ds.augmentor = audio_augmentations
Am I correct and thanks @okuchaiev
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Yes, code looks fine to me. But for impulse you should use impulse pertubation not noise pertubation.
Sample can be found here:
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@nithinraok that's what I thought, However in Titanet-Large they use noise instead of impulse, and it says we are using impulse perturbation. So, does that mean in their training they made an error using RIR corpora for noise instead of pulse perturbation.
NeMo/examples/speaker_tasks/recognition/conf/titanet-large.yaml
Lines 14 to 26 in 6442bb6
The paper statement:
(just realized you are the first author x.x)
Thank you @nithinraok
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I don;t remember details exactly but as far I remember RIR corpora also has noise samples as well along with impulse responses, and I have not added impulse section to this config file but was added to titanet-small config.
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