97 datasets found

The TEDLIUM corpus is a large-volume corpus used for speech recognition and text summarization.

A hybrid CNN-BiLSTM VOICE ACTIVITY DETECTOR for voice activity detection (VAD) incorporating both convolutional neural network (CNN) and bidirectional long short-term memory...

The dataset used in this paper is a collection of phonetically and phonologically local allophonic distribution in English, where voiceless stops surface as aspirated...

The TIMIT corpus is a widely used benchmark for speech recognition tasks. It contains 3,696 training utterances from 462 speakers, excluding the SA sentences. The core test set...

The dataset used for testing the AniTalker framework, containing 4,242 unique speaker IDs, 17,108 video clips, and a cumulative duration of 55 hours.

AMI dataset for speaker diarization and recognition

Multi-scale octave convolutional layers for robust speech recognition

The LRS2 dataset consists of 48,164 video clips from outdoor shows on BBC television. Each video is accompanied by an audio corresponding to a sentence with up to 100 characters.

The AMI Meeting Corpus was collected in three instrumented rooms with meeting conversations. Each room has two microphone arrays to collect 100 hours of far-field...

The Voice Bank Corpus is a large regional accent speech database containing over 10 hours of speech data from 20 speakers.

A dataset for Sanskrit ASR

A new Sanskrit speech corpus and a large-vocabulary ASR system for Sanskrit

The Google Speech Command Dataset is a dataset for keyword spotting, which is a task in speech recognition. The dataset contains 12 classes, including 10 keywords and two extra...

The CHiME-4 dataset is a large-scale speech recognition dataset, containing over 2 hours of speech from 6 channels.

Aurora-4 dataset is a broadband corpus designed for noisy speech recognition tasks based on the Wall Street Journal (WSJ0) corpus.

The Switchboard corpus is a dataset of speech recordings from a switchboard, which is a device that allows multiple people to speak at the same time.

The dataset used in the paper is the Libri-Light dataset, which is a subset of the LibriSpeech dataset. The authors used this dataset to pre-train their proposed dual-mode ASR...

The dataset used for the task of mispronunciation detection for second language learners.

The proposed method uses the acoustic unit (AU) as the intermediary feature for both mispronunciation detection and correction.

The TIMIT acoustic-phonetic continuous speech corpusCD-ROM contains a large collection of speech samples from 250 male and 250 female speakers.