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 2951–2975 of 3012 papers

TitleStatusHype
Causal Analysis of ASR Errors for Children: Quantifying the Impact of Physiological, Cognitive, and Extrinsic Factors—0
Causal Structure Discovery for Error Diagnostics of Children's ASR—0
A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting—0
CEASR: A Corpus for Evaluating Automatic Speech Recognition—0
Chain of Correction for Full-text Speech Recognition with Large Language Models—0
Chain-of-Thought Prompting for Speech Translation—0
Challenges and Opportunities in Multi-device Speech Processing—0
Challenges and Opportunities of Speech Recognition for Bengali Language—0
Challenges in Speech Recognition and Translation of High-Value Low-Density Polysynthetic Languages—0
Challenges of Applying Automatic Speech Recognition for Transcribing EU Parliament Committee Meetings: A Pilot Study—0
Challenges of Computational Processing of Code-Switching—0
Chameleon: A Language Model Adaptation Toolkit for Automatic Speech Recognition of Conversational Speech—0
Characterizing Audio Adversarial Examples Using Temporal Dependency—0
Characterizing Speech Adversarial Examples Using Self-Attention U-Net Enhancement—0
Chinese-LiPS: A Chinese audio-visual speech recognition dataset with Lip-reading and Presentation Slides—0
Chinese Medical Speech Recognition with Punctuated Hypothesis—0
Citrinet: Closing the Gap between Non-Autoregressive and Autoregressive End-to-End Models for Automatic Speech Recognition—0
Classification of Closely Related Sub-dialects of Arabic Using Support-Vector Machines—0
Cleanformer: A multichannel array configuration-invariant neural enhancement frontend for ASR in smart speakers—0
Clinical BERTScore: An Improved Measure of Automatic Speech Recognition Performance in Clinical Settings—0
Clinical Dialogue Transcription Error Correction using Seq2Seq Models—0
Cloud-based Automatic Speech Recognition Systems for Southeast Asian Languages—0
CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments—0
Coarse-To-Fine And Cross-Lingual ASR Transfer—0
Codec-ASR: Training Performant Automatic Speech Recognition Systems with Discrete Speech Representations—0
Show:102550
← PrevPage 119 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