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 45514600 of 6433 papers

TitleStatusHype
Investigating Target Set Reduction for End-to-End Speech Recognition of Hindi-English Code-Switching Data0
Comparison of Neural Network Architectures for Spectrum Sensing0
Hierarchical Sequence to Sequence Voice Conversion with Limited Data0
Learn Spelling from Teachers: Transferring Knowledge from Language Models to Sequence-to-Sequence Speech Recognition0
PyKaldi2: Yet another speech toolkit based on Kaldi and PyTorchCode0
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition0
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition0
Multi-layer Attention Mechanism for Speech Keyword Recognition0
Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition0
M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention0
Joint Speech Recognition and Speaker Diarization via Sequence Transduction0
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech RecognitionCode0
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation0
Teach an all-rounder with experts in different domains0
Transfer Learning from Audio-Visual Grounding to Speech Recognition0
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning0
NIESR: Nuisance Invariant End-to-end Speech RecognitionCode0
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training0
Toward Fairness in AI for People with Disabilities: A Research Roadmap0
End-to-End Speech Recognition with High-Frame-Rate Features Extraction0
Kite: Automatic speech recognition for unmanned aerial vehicles0
Scalable Multi Corpora Neural Language Models for ASR0
Latent Dirichlet Allocation Based Acoustic Data Selection for Automatic Speech Recognition0
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization0
Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies0
Deep Bayesian Natural Language Processing0
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR0
Improving Performance of End-to-End ASR on Numeric Sequences0
Apport de l'adaptation automatique des mod\`eles de langage pour la reconnaissance de la parole: \'evaluation qualitative extrins\`eque dans un contexte de traitement de cours magistraux (Contribution of automatic adaptation of language models for speech recognition : extrinsic qualitative evaluation in a context of educational courses)0
An adaptable task-oriented dialog system for stand-alone embedded devices0
Analyzing Utility of Visual Context in Multimodal Speech Recognition Under Noisy Conditions0
Gated Embeddings in End-to-End Speech Recognition for Conversational-Context Fusion0
One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers0
Essence Knowledge Distillation for Speech Recognition0
Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition0
A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks0
Machine Learning Construction: implications to cybersecurity0
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural NetworksCode0
Phoneme-Based Contextualization for Cross-Lingual Speech Recognition in End-to-End Models0
Database Meets Deep Learning: Challenges and Opportunities0
Multi-Span Acoustic Modelling using Raw Waveform Signals0
Integration of TensorFlow based Acoustic Model with Kaldi WFST Decoder0
A simple and effective postprocessing method for image classification0
Code-Switching Detection Using ASR-Generated Language Posteriors0
Multi-Graph Decoding for Code-Switching ASR0
Real to H-space Encoder for Speech Recognition0
Speech Recognition With No Speech Or With Noisy Speech Beyond English0
Advancing Speech Recognition With No Speech Or With Noisy Speech0
Adversarial Training for Multilingual Acoustic Modeling0
Multi-Stream End-to-End 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