160 datasets found

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...

Language models have been commonly adopted to boost the performance of automatic speech recognition (ASR) particularly in domain adaptation tasks. Conventional way of LM...

The dataset used in the paper is the AudioMNIST dataset, which contains 30,000 audio recordings.

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.

Tedlium3: A large-scale English speech corpus for speaker adaptation.

The GTZAN dataset is a small but popular dataset for genre classification, containing 10 musical genres, with each genre having 100 audio snippets of 30 s length.

The dataset is a collection of 8kHz audio recordings of spoken digits from 'zero' to 'nine'.

Collecting and evaluating speech recognition corpora for nine southern bantu languages

The NCHLT speech corpus of the South African languages

The dataset used in this paper is EasyASR, a distributed machine learning platform for end-to-end automatic speech recognition.

The dataset used in this paper is a Conv1D equipped ASR model deployed on mobile devices.

The proposed 2D Conv-Attention model is compared with a traditional neural beamformer and multi-head attention based model.

The People’s Speech: A large-scale diverse English speech recognition dataset for commercial usage.

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.