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Speaker Classification

实战练习

Transformer实战练习，代码见Github仓库。

This is a practice of Transformer, follow the guide of Github Repo.

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Overview​

Classify the speaker of given features, learn how to use Transformer and how to adjust parameters of transformer.

Dataset​

The original dataset is VoxCeleb1.

We randomly select 600 speakers from VoxCeleb1, then preprocess the raw waveforms into mel-spectrograms. You can download the preprocessed dataset from Google Drive.

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Arguments:

  • data_dir: The path to the data directory.

  • metadata_path: The path to the metadata.

  • segment_len: The length of audio segment for training.

The architecture of dataset directory is shown below, where uttr-{random string}.pt represents PyTorch data file containing valid mel-spectrogram data.

data directory/
├── mapping.json
├── metadata.json
├── testdata.json
└── uttr-{random string}.pt

This is also the assignment solution of ML2021Spring HW4.