LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. Note that in order to limit the required storage for preparin...
Scientific papers datasets contains two sets of long and structured documents. The datasets are obtained from ArXiv and PubMed OpenAccess repositories. Both "arxiv" and "pubmed" have two features: - article: the body of the document, pagragraphs seperated by "/n". - abstract: the abstract of the document, pagragraphs seperated by "/n". - ...
Translates SQuAD 2.0 from english to portuguese using Google Cloud API
Translates SQuAD 2.0 from english to portuguese using Google Cloud API
Translates SQuAD 2.0 from english to portuguese using Google Cloud API
Extreme Summarization (XSum) Dataset. There are two features: - document: Input news article. - summary: One sentence summary of the article.
SQuAD_v2_sv is a Swedish version of SQuAD2.0. Translation was done automatically by using Google Translate API but it is not so straightforward because; 1. the span which determines the start and the end of the answer in the context may vary after translation, 2. tne translated context may not contain the translated answer if we translate both ...
Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the `.map()` function as follows: ```python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.rea...
Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the `.map()` function as follows: ```python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.rea...
Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .flac format and is not converted to a float32 array. To convert, the audio file to a float32 array, please make use of the `.map()` function as follows: ```python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.rea...
