194 datasets found

The DIRHA English WSJ dataset is part of the DIRHA project, which focuses on speech interaction in domestic scenes via distant microphones.

The multi-stream paradigm of audio processing, in which several sources are simultaneously considered, has been an active research area for information fusion. The proposed...

Multichannel linear filters for speech recognition in noisy environments

Realistic multi-microphone data simulation for distant speech recognition

The ICSI Meeting Corpus

The Corpus of Spontaneous Japanese: Its design and evaluation [30] is a dataset of spontaneous Japanese speech.

The MSR dataset is a widely used vulnerability detection dataset, consisting of 10,900 vulnerable examples and 177,736 non-vulnerable examples.

The dataset used in this paper is the English Broadcast News (BN) dataset.

Deep Convolutional Neural Networks (CNNs) are more powerful than Deep Neural Networks (DNN), as they are able to better reduce spectral variation in the input signal.

The Korean GEC dataset, which includes text-level errors and is used to construct the ASR Post-Processing dataset.

The proposed text-level error type classification criteria, which considers 13 text-level errors that can occur in speech recognition situations.

The proposed speech-level error type classification criteria, which considers 24 sub-types for noise error and 13 sub-types for speaker characteristics.

The proposed Error Explainable Benchmark (EEB) dataset, which considers both speech- and text-level error types, to diagnose and validate ASR models and post-processors.

The dataset used for the speech translation task, which consists of multilingual speech data.

The SLR41 and SLR44 datasets consist of pairs of audio recordings and corresponding transcripts.

The SLR35 and SLR36 datasets consist of 200,000 speech recordings from native speakers.

The Magic Data dataset consists of 3.5 hours of Indonesian scripted speeches from 10 people.

The study uses the TITML-IDN, Magic Data, Common Voice, SLR35, SLR36, SLR41, and SLR44 datasets for training and evaluation of the ASR system.

The Airbus dataset contains transcripts of ATC speech from the Vienna airport together with surveil-lance call-signs for each transcript.

The Malorca dataset consists of transcripts of ATC speech from the Vienna airport together with surveil-lance call-signs for each transcript. The LiveATC dataset contains...