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 38013850 of 6433 papers

TitleStatusHype
The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning0
A Study on Lip Localization Techniques used for Lip reading from a Video0
FluentNet: End-to-End Detection of Speech Disfluency with Deep Learning0
Estimation error analysis of deep learning on the regression problem on the variable exponent Besov space0
A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition BaselineCode1
End-to-End Speech Recognition and Disfluency RemovalCode1
End-to-End Learning of Speech 2D Feature-Trajectory for Prosthetic HandsCode0
Consecutive Decoding for Speech-to-text TranslationCode1
An analysis of deep neural networks for predicting trends in time series data0
Monolingual Data Selection Analysis for English-Mandarin Hybrid Code-switching Speech Recognition0
EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition0
SWP-LeafNET: A novel multistage approach for plant leaf identification based on deep CNN0
Multi-modal embeddings using multi-task learning for emotion recognition0
VoiceFilter-Lite: Streaming Targeted Voice Separation for On-Device Speech RecognitionCode2
Unmanned Aerial Vehicle Control Through Domain-based Automatic Speech Recognition0
An End-to-end Architecture of Online Multi-channel Speech Separation0
KoSpeech: Open-Source Toolkit for End-to-End Korean Speech RecognitionCode1
Robust Spoken Language Understanding with RL-based Value Error Recovery0
Libri-Adapt: A New Speech Dataset for Unsupervised Domain AdaptationCode1
Any-to-Many Voice Conversion with Location-Relative Sequence-to-Sequence ModelingCode1
Silent Speech Interfaces for Speech Restoration: A Review0
Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody Transfer0
Fine-grained Early Frequency Attention for Deep Speaker Representation Learning0
Estimating the Brittleness of AI: Safety Integrity Levels and the Need for Testing Out-Of-Distribution Performance0
Convolutional Speech Recognition with Pitch and Voice Quality Features0
Innovative Pretrained-based Reranking Language Models for N-best Speech Recognition Lists0
Nepali Speech Recognition Using CNN, GRU and CTC0
A Preliminary Study on Leveraging Meta Learning Technique for Code-switching Speech Recognition0
Taiwanese Speech Recognition Based on Hybrid Deep Neural Network Architecture0
Multi-view Attention-based Speech Enhancement Model for Noise-robust Automatic Speech Recognition0
Hearings and mishearings: decrypting the spoken word0
Survey of Machine Learning Accelerators0
A Survey of Deep Active LearningCode0
Parallel Rescoring with Transformer for Streaming On-Device Speech Recognition0
Data augmentation using prosody and false starts to recognize non-native children's speechCode0
Optimising AI Training Deployments using Graph Compilers and Containers0
Learned Transferable Architectures Can Surpass Hand-Designed Architectures for Large Scale Speech Recognition0
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts0
A Survey on Evolutionary Neural Architecture Search0
Machine Semiotics0
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus0
Cross-Utterance Language Models with Acoustic Error Sampling0
Compiling ONNX Neural Network Models Using MLIRCode1
A Real-time Robot-based Auxiliary System for Risk Evaluation of COVID-19 Infection0
Are Neural Open-Domain Dialog Systems Robust to Speech Recognition Errors in the Dialog History? An Empirical StudyCode0
Computer-Generated Music for Tabletop Role-Playing GamesCode1
Speech To Semantics: Improve ASR and NLU Jointly via All-Neural Interfaces0
Adaptation Algorithms for Neural Network-Based Speech Recognition: An OverviewCode0
Sum-Product Networks for Robust Automatic Speaker IdentificationCode1
LSTM Acoustic Models Learn to Align and Pronounce with Graphemes0
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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