There are several methods for creating and sharing an audio dataset: Create an audio dataset from local files in python with Dataset.push_to_hub().

It consists of TAR archives containing audio files and their metadata and is optimized for streaming. It is useful if you have a large number of audio files and ...

15 дек. 2022 г. · LibriSpeech is a standard large-scale dataset for evaluating ASR systems. It consists of approximately 1,000 hours of narrated audiobooks ...

In this course we will use the Datasets library to work with audio datasets. Datasets is an open-source library for downloading and preparing datasets ...

You can pick any dataset on the Hub, scroll through the samples and listen to the audio for the different subsets and splits, gauging whether it's the right ...

You can load an audio dataset using the Audio feature that automatically decodes and resamples the audio files when you access the examples. Audio decoding is ...

Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources.

First, the Whisper feature extractor pads/truncates a batch of audio examples such that all examples have an input length of 30s. Examples shorter than this are ...

The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools ...

This guide shows specific methods for processing audio datasets. Learn how to: Resample the sampling rate. Use map() with audio datasets.