Titanet-L Augmentation about nemo HOT 4 OPEN

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

from nemo.

Yes, code looks fine to me. But for impulse you should use impulse pertubation not noise pertubation.
Sample can be found here:

from nemo.

@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.

The paper statement:

(just realized you are the first author x.x)
Thank you @nithinraok

from nemo.

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.

from nemo.