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 426–450 of 3012 papers

TitleStatusHype
A Universally-Deployable ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement, and Voice Separation—0
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
Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies—0
Automated scoring across different modalities—0
Automated speech tools for helping communities process restricted-access corpora for language revival efforts—0
Automated speech-unit delimitation in spoken learner English—0
Automatically Assess Children's Reading Skills—0
Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics—0
Automatic assessment of spoken language proficiency of non-native children—0
Automatic Detection of Code-switching Style from Acoustics—0
All-neural beamformer for continuous speech separation—0
Automatic Documentation of ICD Codes with Far-Field Speech Recognition—0
A two-stage transliteration approach to improve performance of a multilingual ASR—0
Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish—0
Automatic Learning of Subword Dependent Model Scales—0
Automatic Quality Estimation for ASR System Combination—0
Automatic recognition and detection of aphasic natural speech—0
Automatic recognition of child speech for robotic applications in noisy environments—0
Automatic recognition of element classes and boundaries in the birdsong with variable sequences—0
Automatic recognition of suprasegmentals in speech—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
Analyzing ASR pretraining for low-resource speech-to-text translation—0
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation—0
Show:102550
← PrevPage 18 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