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 41514200 of 6433 papers

TitleStatusHype
Smart Computer Aided Translation Environment - SCATE0
SmarTerp: A CAI System to Support Simultaneous Interpreters in Real-Time0
Smart Speech Segmentation using Acousto-Linguistic Features with look-ahead0
SMILEE: Symmetric Multi-modal Interactions with Language-gesture Enabled (AI) Embodiment0
Smoothed marginal distribution constraints for language modeling0
SNDCNN: Self-normalizing deep CNNs with scaled exponential linear units for speech recognition0
Snow Mountain: Dataset of Audio Recordings of The Bible in Low Resource Languages0
SNRi Target Training for Joint Speech Enhancement and Recognition0
Socially-Aware Animated Intelligent Personal Assistant Agent0
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition0
Soft Random Sampling: A Theoretical and Empirical Analysis0
Solving Tensor Low Cycle Rank Approximation0
Solving Verbal Questions in IQ Test by Knowledge-Powered Word Embedding0
Some voices are too common: Building fair speech recognition systems using the Common Voice dataset0
Sonos Voice Control Bias Assessment Dataset: A Methodology for Demographic Bias Assessment in Voice Assistants0
SOPA: Random Forests Regression for the Semantic Textual Similarity task0
SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks0
Sotto Voce: Federated Speech Recognition with Differential Privacy Guarantees0
SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation0
Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation0
``So, which one is it?'' The effect of alternative incremental architectures in a high-performance game-playing agent0
Space-Efficient Representation of Entity-centric Query Language Models0
Space-time error estimates for deep neural network approximations for differential equations0
Sparsely Shared LoRA on Whisper for Child Speech Recognition0
Sparse Non-negative Matrix Language Modeling0
Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip0
Sparse Transcription0
SparseVSR: Lightweight and Noise Robust Visual Speech Recognition0
Sparsification via Compressed Sensing for Automatic Speech Recognition0
Sparsifying Networks via Subdifferential Inclusion0
Spartus: A 9.4 TOp/s FPGA-based LSTM Accelerator Exploiting Spatio-Temporal Sparsity0
Spatial Audio Processing with Large Language Model on Wearable Devices0
Spatial Correlation and Value Prediction in Convolutional Neural Networks0
Spatial Diffuseness Features for DNN-Based Speech Recognition in Noisy and Reverberant Environments0
Spatio-Temporal Attention Mechanism and Knowledge Distillation for Lip Reading0
Spatio-Temporal Fusion Based Convolutional Sequence Learning for Lip Reading0
Speaker Adaptation for Attention-Based End-to-End Speech Recognition0
Speaker Adaptation for End-to-End CTC Models0
Speaker adaptation for Wav2vec2 based dysarthric ASR0
Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition0
Speaker Adapted Beamforming for Multi-Channel Automatic Speech Recognition0
Speaker-Adapted End-to-End Visual Speech Recognition for Continuous Spanish0
Speaker- and Age-Invariant Training for Child Acoustic Modeling Using Adversarial Multi-Task Learning0
Speaker and Language Change Detection using Wav2vec2 and Whisper0
Speaker Anonymization with Phonetic Intermediate Representations0
Speaker-aware speech-transformer0
Speaker Change Detection for Transformer Transducer ASR0
Speaker Cluster-Based Speaker Adaptive Training for Deep Neural Network Acoustic Modeling0
Speaker conditioning of acoustic models using affine transformation for multi-speaker speech recognition0
Speaker conditioned acoustic modeling for multi-speaker conversational ASR0
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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