97 datasets found

The accented English speech recognition challenge 2020: Open datasets, tracks, baselines, results and methods.

GigaSpeech: An evolving, multi-domain ASR corpus with 10,000 hours of transcribed audio.

TED-LIUM 3 (TL3) is a TED talks dataset. Speaker adaptation data for TL3 was divided randomly, where 2/5 was divided into the train set, 1/5 was divided into the dev set, and...

The ASRU 2019 Mandarin-English code-switching speech recognition challenge dataset.

The Wall Street Journal dataset is used for syntactic linearization. It contains a large corpus of news articles with their corresponding syntactic trees.

A corpus of free and representative video content was gathered. This corpus includes videos having progressive scanning, 1280x720 resolution, and framerates between 24-30 frames...

The Speech Recognition dataset is used for speech recognition tasks.

The dataset used for performing continuous speech recognition experiments using EEG features.

The dataset used for performing isolated and continuous speech recognition experiments using EEG features.

LibriSpeech: an ASR corpus based on public domain audio books.

Libriheavy is a large-scale ASR corpus consisting of 50,000 hours of read English speech derived from LibriVox. To the best of our knowledge, Libriheavy is the largest...

The CHiME-2 dataset is a speech separation and recognition challenge dataset. It contains 7138 utterances of 8 speakers, each with 10 seconds of speech.

The MHINT corpus is a Mandarin Chinese speech corpus used for speech recognition and speech enhancement. It contains 480 utterances of 10 speakers, each with 10 seconds of speech.

DeepMine is a Persian speech corpus.

Google Speech Command (GSC) is a dataset for limited-vocabulary speech recognition.

The ATIS dataset is a benchmark dataset for spoken language understanding, consisting of audio recordings and corresponding manual transcripts about humans asking for flight...

This work showcases a cost-effective method for generating training data for speech processing tasks. The dataset UK-PODS-ALIGN is a dataset that features modern conversational...

This work showcases a cost-effective method for generating training data for speech processing tasks. The dataset MCV-10 is a multilingual dataset that contains 50 hours of...

This work showcases a cost-effective method for generating training data for speech processing tasks. The dataset UK-PODS features modern conversational Ukrainian language.

The TIMIT corpus is a large database of speech recordings used for speaker recognition and speech synthesis tasks.