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 32013250 of 6433 papers

TitleStatusHype
Word-Free Spoken Language Understanding for Mandarin-Chinese0
Combining Frame-Synchronous and Label-Synchronous Systems for Speech RecognitionCode1
StableEmit: Selection Probability Discount for Reducing Emission Latency of Streaming Monotonic Attention ASR0
ESPnet-ST IWSLT 2021 Offline Speech Translation System0
Sequence-level Confidence Classifier for ASR Utterance Accuracy and Application to Acoustic Models0
On joint training with interfaces for spoken language understanding0
IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task0
Rethinking End-to-End Evaluation of Decomposable Tasks: A Case Study on Spoken Language Understanding0
On a novel training algorithm for sequence-to-sequence predictive recurrent networks0
Use of Machine Learning Technique to maximize the signal over background for H ττ0
Building Intelligent Autonomous Navigation Agents0
Lexical Access Model for Italian -- Modeling human speech processing: identification of words in running speech toward lexical access based on the detection of landmarks and other acoustic cues to features0
QASR: QCRI Aljazeera Speech Resource -- A Large Scale Annotated Arabic Speech Corpus0
Where are we in semantic concept extraction for Spoken Language Understanding?0
Mixtures of Deep Neural Experts for Automated Speech Scoring0
Zero-Shot Joint Modeling of Multiple Spoken-Text-Style Conversion Tasks using Switching Tokens0
How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures0
MeshRIR: A Dataset of Room Impulse Responses on Meshed Grid Points For Evaluating Sound Field Analysis and Synthesis MethodsCode1
A Discriminative Entity-Aware Language Model for Virtual Assistants0
Pay Better Attention to Attention: Head Selection in Multilingual and Multi-Domain Sequence Modeling0
Learning From the Master: Distilling Cross-Modal Advanced Knowledge for Lip Reading0
Analysis and Tuning of a Voice Assistant System for Dysfluent Speech0
On-Device Personalization of Automatic Speech Recognition Models for Disordered Speech0
An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition0
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System0
Multi-mode Transformer Transducer with Stochastic Future Context0
Layer Pruning on Demand with Intermediate CTC0
Best Practices for Noise-Based Augmentation to Improve the Performance of Deployable Speech-Based Emotion Recognition Systems0
Topic Classification on Spoken Documents Using Deep Acoustic and Linguistic Features0
Collaborative Training of Acoustic Encoders for Speech Recognition0
Semantic sentence similarity: size does not always matter0
Multi-Speaker ASR Combining Non-Autoregressive Conformer CTC and Conditional Speaker ChainCode0
Momentum Pseudo-Labeling for Semi-Supervised Speech RecognitionCode0
Efficient Deep Learning: A Survey on Making Deep Learning Models Smaller, Faster, and BetterCode1
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition0
RyanSpeech: A Corpus for Conversational Text-to-Speech SynthesisCode1
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling0
Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget0
Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft's Submission to SwissText 20210
Assessing the Use of Prosody in Constituency Parsing of Imperfect TranscriptsCode0
Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition0
Learning Audio-Visual DereverberationCode1
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts0
CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition0
SynthASR: Unlocking Synthetic Data for Speech Recognition0
Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition0
Dynamic Gradient Aggregation for Federated Domain Adaptation0
Audio Attacks and Defenses against AED Systems -- A Practical Study0
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsCode1
Show:102550
← PrevPage 65 of 129Next →

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