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A ready-to-use pytorch dataloader for audio classification, speech classification, speaker recognition, etc. with in-GPU augmentations.

• PyTorch speech dataloader with 5 (or less) lines of code.get_torch_speech_dataloader_from_config(config)
• Batch augmentation in GPU, powered bytorch-audiomentations
• RIRs augmentation with any set of IR file(s) [cpu]
• MUSAN-like augmentation with any set of source files. Customizable. [cpu]
• Written in one night, may contain bugs!

pip install -U git+https://github.com/zabir-nabil/torch-speech-dataloader.git@main

fromtorch_speech_dataloaderimportget_torch_speech_dataloader,get_torch_speech_dataloader_from_configfromtorch_speech_dataloader.augmentation_utilsimportplaceholder_gpu_augmentationconfig_1= {"filenames" : ["../test.wav"]*5+ ["../test_hindi.wav"]*5,"speech_labels" : ["test"]*5+ ["test2"]*5,"batch_size" :3,"num_workers" :5,"device" :torch.device('cuda:1'),"sanity_check_path" :"../sanity_test","sanity_check_samples" :2,"batch_audio_augmentation":placeholder_gpu_augmentation,"rirs_reverb" : {"apply":True},"musan_augmentation" : {"apply":True,"mix_multiples_max_count":-1,"musan_max_len":1.},"verbose" :0}dummy_tsdl=get_torch_speech_dataloader_from_config(config_1)ford,lindummy_tsdl.get_batch():print(d.shape)print(l)

• filenames: A list of filepaths for the audio / speech files (usually wav).
• speech_labels: Corresponding labels forfilenames / list of audio files.
• batch_size: Batch size of the dataloader.
• num_workers: Dataloader workers.
• device: torch device [default:cpu].
• sanity_check_path: If you want to look at the sample audio files generated, specify a path where the sample augmented audio files will be saved.
• sanity_check_samples: Number of sample audio files to store in the sanity check folder.
• batch_audio_augmentation: Usually, it will run on the GPU batch if gpu device is specified, else on the CPU batch. Any transform (compose) / augmentation, that takes a tensor of dimension[B x C x N].
• rirs_reverb:
  • apply: If apply is true, only then this augmentation will be applied to each audio individually.
  • reverb_source_files_path: A list of IR filepaths.
• musan_augmentation:
  • apply: If apply is true, only then this augmentation will be applied to each audio individually.
  • musan_config:{ "music": ([list of music file paths], range_for_num_music_files_to_use, range_for_noise_snr), "speech": ([list of speech file paths], range_for_num_speech_files_to_use, range_for_noise_snr), }[example: augmentation_utils.placeholder_musan_config]
  • mix_multiples_max_count: Multiple noise types should be mixed (music + noise +...). Number of noise types that should be mixed at most.
  • musan_max_len:<= 0: take the musan noise and crop it with equal length (same as input audio);> 0: maximum length of the cropped musan noise (in secs.).
• audio_augmentation: List offuncs that can be applied to a single audio with shape[N,].
• features: Feature extraction.[N,] ->[T,F].
• feature_augmentation: List offuncs that can be applied to a single feature with shape[T,F].