SOTAVerified

Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 751–775 of 3012 papers

TitleStatusHype
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition—0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications—0
All-neural beamformer for continuous speech separation—0
A two-stage transliteration approach to improve performance of a multilingual ASR—0
A Likelihood Ratio based Domain Adaptation Method for E2E Models—0
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition—0
Attentive listening system with backchanneling, response generation and flexible turn-taking—0
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation—0
Attentive Adversarial Learning for Domain-Invariant Training—0
Attention Enhanced Citrinet for Speech Recognition—0
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework—0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms—0
A Closer Look at Audio-Visual Multi-Person Speech Recognition and Active Speaker Selection—0
Attention-based Wav2Text with Feature Transfer Learning—0
Attention based on-device streaming speech recognition with large speech corpus—0
Alignment Restricted Streaming Recurrent Neural Network Transducer—0
Attention based end to end Speech Recognition for Voice Search in Hindi and English—0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition—0
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition—0
Correlated Bigram LSA for Unsupervised Language Model Adaptation—0
Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model—0
Correction Focused Language Model Training for Speech Recognition—0
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models—0
Alignment-Free Training for Transducer-based Multi-Talker ASR—0
Corpus Phonetics Tutorial—0
Show:102550
← PrevPage 31 of 121Next →
All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1—Unverified
2TM-seq2seqTest WER9.7—Unverified
3CTC/attentionTest WER8.2—Unverified
4LF-MMI TDNNTest WER6.7—Unverified
5Whisper-LLaMATest WER6.6—Unverified
6End2end ConformerTest WER3.9—Unverified
7End2end ConformerTest WER3.7—Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7—Unverified
9CTC/AttentionTest WER1.5—Unverified
10WhisperTest WER1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5—Unverified
2CleanMel-L-maskCER14.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32—Unverified
2Whisper-largev3-finetunedTest WER10.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89—Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98—Unverified