SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 16511700 of 6433 papers

TitleStatusHype
Decoupling recognition and transcription in Mandarin ASR0
Design and Development of Speech Corpora for Air Traffic Control Training0
Detecting Mild Cognitive Impairment by Exploiting Linguistic Information from Transcripts0
Deep Bayesian Natural Language Processing0
Development of a TV Broadcasts Speech Recognition System for Qatari Arabic0
Cloud-Based Face and Speech Recognition for Access Control Applications0
DeepCon: An End-to-End Multilingual Toolkit for Automatic Minuting of Multi-Party Dialogues0
Deep context: end-to-end contextual speech recognition0
A Research Platform for Multi-Robot Dialogue with Humans0
Audio-visual Multi-channel Recognition of Overlapped Speech0
Audio-visual multi-channel speech separation, dereverberation and recognition0
Deep Double-Side Learning Ensemble Model for Few-Shot Parkinson Speech Recognition0
Cloud-based Automatic Speech Recognition Systems for Southeast Asian Languages0
Closing the Gap Between Time-Domain Multi-Channel Speech Enhancement on Real and Simulation Conditions0
Advocating Character Error Rate for Multilingual ASR Evaluation0
Deep Feed-forward Sequential Memory Networks for Speech Synthesis0
A Mixture of Expert Based Deep Neural Network for Improved ASR0
Adapter-Based Multi-Agent AVSR Extension for Pre-Trained ASR Models0
Audio-Visual Speech and Gesture Recognition by Sensors of Mobile Devices0
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition0
Acoustic and Textual Data Augmentation for Improved ASR of Code-Switching Speech0
Closing the Gap between Single-User and Multi-User VoiceFilter-Lite0
Deep Learning and Continuous Representations for Natural Language Processing0
Deep learning and face recognition: the state of the art0
Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning0
Estimation of a function of low local dimensionality by deep neural networks0
Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI0
ParasNet: Fast Parasites Detection with Neural Networks0
Deep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition0
Deep Learning based Multi-Source Localization with Source Splitting and its Effectiveness in Multi-Talker Speech Recognition0
Deep Learning-based Spatio Temporal Facial Feature Visual Speech Recognition0
Clipping Free Attacks Against Neural Networks0
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition0
Deep Learning for Computational Chemistry0
Deep Learning for Dialogue Systems0
Deep Learning for Distant Speech Recognition0
Deep Learning for Environmentally Robust Speech Recognition: An Overview of Recent Developments0
Deep Learning for Forecasting Stock Returns in the Cross-Section0
Deep Learning for Lip Reading using Audio-Visual Information for Urdu Language0
Deep Learning for Pathological Speech: A Survey0
Deep Learning for Punctuation Restoration in Medical Reports0
Deep Learning for Single and Multi-Session i-Vector Speaker Recognition0
Deep Learning for Social Media Health Text Classification0
Deep Learning for Time-Series Analysis0
Clipping free attacks against artificial neural networks0
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period0
Deep Learning in Proteomics Informatics: Applications, Challenges, and Future Directions0
Deep Learning in the Automotive Industry: Applications and Tools0
Augmenting Polish Automatic Speech Recognition System With Synthetic Data0
ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified