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 47014750 of 6433 papers

TitleStatusHype
VideoBERT: A Joint Model for Video and Language Representation LearningCode0
Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than Others0
End-to-End Visual Speech Recognition for Small-Scale Datasets0
Unsupervised training of neural mask-based beamforming0
Learning Shared Encoding Representation for End-to-End Speech Recognition Models0
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition0
Modeling Acoustic-Prosodic Cues for Word Importance Prediction in Spoken Dialogues0
Wasserstein Dependency Measure for Representation Learning0
Automatic Spelling Correction with Transformer for CTC-based End-to-End Speech Recognition0
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech RecognitionCode0
Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
Audio De-identification: A New Entity Recognition Task0
Automatic assessment of spoken language proficiency of non-native children0
Audiovisual Speaker Tracking using Nonlinear Dynamical Systems with Dynamic Stream WeightsCode0
End-To-End Speech Recognition Using A High Rank LSTM-CTC Based ModelCode0
Bootstrapping Method for Developing Part-of-Speech Tagged Corpus in Low Resource Languages Tagset - A Focus on an African Igbo0
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling0
Singing voice conversion with non-parallel data0
Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling0
The Virtual Doctor: An Interactive Artificial Intelligence based on Deep Learning for Non-Invasive Prediction of Diabetes0
Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language Models0
Speech Recognition with no speech or with noisy speech0
KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube VideosCode0
Context-aware Neural-based Dialog Act Classification on Automatically Generated Transcriptions0
Incorporating End-to-End Speech Recognition Models for Sentiment Analysis0
All-neural online source separation, counting, and diarization for meeting analysis0
The NIGENS General Sound Events Database0
Learning with Inadequate and Incorrect Supervision0
Audio-Linguistic Embeddings for Spoken SentencesCode0
A spelling correction model for end-to-end speech recognition0
Learned In Speech Recognition: Contextual Acoustic Word Embeddings0
Self-Attention Aligner: A Latency-Control End-to-End Model for ASR Using Self-Attention Network and Chunk-Hopping0
Enhanced Robot Speech Recognition Using Biomimetic Binaural Sound Source Localization0
Towards a Robust Deep Neural Network in Texts: A Survey0
Deep learning and face recognition: the state of the art0
End-to-end Anchored Speech Recognition0
On the Choice of Modeling Unit for Sequence-to-Sequence Speech RecognitionCode0
Using multi-task learning to improve the performance of acoustic-to-word and conventional hybrid models0
Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM0
Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech RecognitionCode0
A Convolutional Neural Network model based on Neutrosophy for Noisy Speech Recognition0
Progressive Label Distillation: Learning Input-Efficient Deep Neural Networks0
Discovery of Important Subsequences in Electrocardiogram Beats Using the Nearest Neighbour Algorithm0
Weighted-Sampling Audio Adversarial Example Attack0
Self-Attention Networks for Connectionist Temporal Classification in Speech RecognitionCode0
Overfitting Mechanism and Avoidance in Deep Neural Networks0
Predicting Performance using Approximate State Space Model for Liquid State Machines0
A Survey of the Recent Architectures of Deep Convolutional Neural Networks0
Phoneme-Based Persian Speech Recognition0
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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