194 datasets found

The dataset used in the paper is a list of active words at each node of the speech recognition system. It is used to evaluate the performance of the speech recognition system...

The dataset used in the paper is a speech recognition dataset for a menu-based speech solution. It contains a list of active words at each node of the speech recognition system.

South African English and Luganda datasets

Radio browsing system for humanitarian relief

ASR-free keyword spotting in low-resource languages

The 80-hour WSJ and 300-hour Switchboard datasets are used for end-to-end speech recognition.

The Qualcomm Keyword Speech Dataset consists of 4270 utterances belonging to four classes, with variable durations from 0.48s to 1.92s.

Convolutional neural networks (CNNs) are a standard component of many current state-of-the-art Large Vocabulary Continuous Speech Recognition (LVCSR) systems. However, CNNs in...

Speech commands: A dataset for limited-vocabulary speech recognition.

Keyword spotting aims to identify specific keyword audio ut-terances. In recent years, deep convolutional neural networks have been widely utilized in keyword spotting systems.

The CSTR VCTK Corpus is a dataset of speech recordings of 109 speakers, each with 20 utterances.

The Google Speech Commands Dataset contains 64,727 one-second-long utterance files which are recorded and labeled with one of 30 target categories.

Keyword spotting (KWS) plays a critical role in enabling speech-based user interactions on smart devices. Recent developments in the field of deep learning have led to wide...

The sequence-to-sequence approach is widely used in speech recognition (SR) nowadays, and many research works are dedicated to show that their capabilities relying on a single...

Federated Noisy Student Training for Automatic Speech Recognition

The VCTK dataset is a large corpus of speech recordings, each containing a single speaker and a single sentence.

Human speech data comprises a rich set of domain factors such as accent, syntactic and semantic variety, or acoustic environment.

Four different corpora are used for our experiments, which are TIMIT, Aurora-4, AMI, and LibriSpeech. TIMIT contains broadband 16kHz recordings of phonetically-balanced read...

The dataset used in this paper is the BABEL dataset, which contains 10881 motion sequences, with 65926 subsequences and the corresponding textual labels.

The Librispeech dataset is a large-scale speaker-dependent speech corpus containing 1080 hours of speech, 5600 utterances, and 1000 speakers.