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 23512400 of 6433 papers

TitleStatusHype
Composing Finite State Transducers on GPUs0
A Spiking Network that Learns to Extract Spike Signatures from Speech Signals0
A Hardware-Friendly Algorithm for Scalable Training and Deployment of Dimensionality Reduction Models on FPGA0
Complex-Valued Time-Frequency Self-Attention for Speech Dereverberation0
Complex Evolution Recurrent Neural Networks (ceRNNs)0
A spelling correction model for end-to-end speech recognition0
Completely Unsupervised Speech Recognition By A Generative Adversarial Network Harmonized With Iteratively Refined Hidden Markov Models0
A Speech Test Set of Practice Business Presentations with Additional Relevant Texts0
A GrAF-compliant Indonesian Speech Recognition Web Service on the Language Grid for Transcription Crowdsourcing0
Acoustic, Phonetic and Prosodic Features of Parkinson's disease Speech0
Comparison of Time-Frequency Representations for Environmental Sound Classification using Convolutional Neural Networks0
Comparison of Soft and Hard Target RNN-T Distillation for Large-scale ASR0
A Speech-enabled Fixed-phrase Translator for Healthcare Accessibility0
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch0
Comparison of parameters of vowel sounds of russian and english languages0
Comparison of Neural Network Architectures for Spectrum Sensing0
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR0
Ask2Mask: Guided Data Selection for Masked Speech Modeling0
Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning0
Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation0
Accurate and Structured Pruning for Efficient Automatic Speech Recognition0
Comparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary0
Comparison of Gender- and Speaker-adaptive Emotion Recognition0
A singular Riemannian geometry approach to Deep Neural Networks I. Theoretical foundations0
Comparison of echo state network output layer classification methods on noisy data0
Comparison of Decoding Strategies for CTC Acoustic Models0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking0
Comparison of Conventional Hybrid and CTC/Attention Decoders for Continuous Visual Speech Recognition0
Comparing Two Basic Methods for Discriminating Between Similar Languages and Varieties0
Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures0
A Generative Model of a Pronunciation Lexicon for Hindi0
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition0
Comparing performance of different set-covering strategies for linguistic content optimization in speech corpora0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data0
Comparing Grammatical Theories of Code-Mixing0
Comparing Discrete and Continuous Space LLMs for Speech Recognition0
A Simple and Generic Belief Tracking Mechanism for the Dialog State Tracking Challenge: On the believability of observed information0
Comparing CTC and LFMMI for out-of-domain adaptation of wav2vec 2.0 acoustic model0
Comparing Apples to Oranges: LLM-powered Multimodal Intention Prediction in an Object Categorization Task0
A simple and effective postprocessing method for image classification0
Comparing and combining classifiers for self-taught vocal interfaces0
A Silent Speech Decoding System from EEG and EMG with Heterogenous Electrode Configurations0
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks0
Acoustic Modeling Using a Shallow CNN-HTSVM Architecture0
Accurate and Reliable Confidence Estimation Based on Non-Autoregressive End-to-End Speech Recognition System0
Improving noisy student training for low-resource languages in End-to-End ASR using CycleGAN and inter-domain losses0
Comparative Error Analysis of Dialog State Tracking0
Comparative Analysis of the wav2vec 2.0 Feature Extractor0
Comparative Analysis of Polynomial and Rational Approximations of Hyperbolic Tangent Function for VLSI Implementation0
Comparative Analysis of Personalized Voice Activity Detection Systems: Assessing Real-World Effectiveness0
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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