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 1176–1200 of 3012 papers

TitleStatusHype
Improving Noisy Student Training on Non-target Domain Data for Automatic Speech Recognition—0
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR ErrorsCode0
Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition—0
End-to-End Evaluation of a Spoken Dialogue System for Learning Basic Mathematics—0
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR—0
LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers—0
Evaluation of Automated Speech Recognition Systems for Conversational Speech: A Linguistic Perspective—0
Resource-Efficient Transfer Learning From Speech Foundation Model Using Hierarchical Feature Fusion—0
Biased Self-supervised learning for ASR—0
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech—0
Phonetic-assisted Multi-Target Units Modeling for Improving Conformer-Transducer ASR system—0
Streaming Audio-Visual Speech Recognition with Alignment Regularization—0
Leveraging Domain Features for Detecting Adversarial Attacks Against Deep Speech Recognition in Noise—0
Probing Statistical Representations For End-To-End ASR—0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks—0
InterMPL: Momentum Pseudo-Labeling with Intermediate CTC Loss—0
More Speaking or More Speakers?—0
Monolingual Recognizers Fusion for Code-switching Speech Recognition—0
Towards Zero-Shot Code-Switched Speech Recognition—0
BECTRA: Transducer-based End-to-End ASR with BERT-Enhanced Encoder—0
Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems—0
Adapting self-supervised models to multi-talker speech recognition using speaker embeddings—0
A Comparative Study on Multichannel Speaker-Attributed Automatic Speech Recognition in Multi-party Meetings—0
Mandarin-English Code-Switching Speech Recognition System for Specific Domain—0
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students—0
Show:102550
← PrevPage 48 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