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Audio | Telmar

    https://telmar.com/solutions/audio/
    Audio | Telmar. Simplify complex multi-market audio campaigns with Telmar’s Audio solution. Achieve more accurate targeting by defining the best audience from the start of each campaign. Maximize reach and frequency across both traditional and streaming audio platforms. Request a demo. Request a demo.

torchaudio.datasets — Torchaudio 0.10.0 documentation

    https://pytorch.org/audio/stable/datasets.html
    torchaudio.datasets All datasets are subclasses of torch.utils.data.Dataset and have __getitem__ and __len__ methods implemented. Hence, they can all be passed to a torch.utils.data.DataLoader which can load multiple samples parallelly using torch.multiprocessing workers. For example:

Audio manipulation with torchaudio — PyTorch Tutorials …

    https://pytorch.org/tutorials/beginner/audio_preprocessing_tutorial.html
    torchaudio.info function fetches metadata of audio. You can provide a path-like object or file-like object. metadata = torchaudio.info(SAMPLE_WAV_PATH) print(metadata) Out: AudioMetaData (sample_rate=44100, num_frames=109368, num_channels=2, bits_per_sample=16, encoding=PCM_S) Where sample_rate is the sampling rate of the audio

Datasets & DataLoaders — PyTorch Tutorials …

    https://pytorch.org/tutorials/beginner/basics/data_tutorial.html
    PyTorch provides two data primitives: torch.utils.data.DataLoader and torch.utils.data.Dataset that allow you to use pre-loaded datasets as well as your own data. Dataset stores the samples and their corresponding labels, and DataLoader wraps an iterable around the Dataset to enable easy access to the samples.

tflite_model_maker.audio_classifier.DataLoader ...

    https://www.tensorflow.org/lite/api_docs/python/tflite_model_maker/audio_classifier/DataLoader
    AudioDataLoader containing audio spectrogram (or any data type generated by spec.preprocess_ds) and labels. gen_dataset View source gen_dataset ( batch_size=1, is_training=False, shuffle=False, input_pipeline_context=None, preprocess=None, drop_remainder=False ) Generate a shared and batched tf.data.Dataset for training/evaluation. …

Writing Custom Datasets, DataLoaders and ... - PyTorch

    https://pytorch.org/tutorials/beginner/data_loading_tutorial.html
    torch.utils.data.DataLoader is an iterator which provides all these features. Parameters used below should be clear. One parameter of interest is collate_fn. You can specify how exactly the samples need to be batched using collate_fn. However, default …

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