In this challenge the task is to learn to recognize which of several English words is pronounced in an audio recording. This is a multiclass classification task.
The dataset is available for download on Canvas. It contains the following files:
- wav.tgz: a compressed directory with all the recordings (training and test data) in the form of wav files.
- feat.npy: an array with Mel-frequency cepstral coefficients extracted from each wav file. The features at index i in this array were extracted from the wav file at index i of the array in the file path.npy.
- path.npy: an array with the order of wav files in the feat.npy array.
- train.csv: this file contains two columns: path with the filename of the recording and word with word which was pronounced in the recording. This is the training portion of the data.
- test.csv: This is the testing portion of the data, and it has the same format as the file train.csv except that the column word is absent.