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 1751–1775 of 3012 papers

TitleStatusHype
Momentum Pseudo-Labeling for Semi-Supervised Speech RecognitionCode0
Multi-Speaker ASR Combining Non-Autoregressive Conformer CTC and Conditional Speaker ChainCode0
Topic Classification on Spoken Documents Using Deep Acoustic and Linguistic Features—0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling—0
A Study into Pre-training Strategies for Spoken Language Understanding on Dysarthric Speech—0
Multi-channel Opus compression for far-field automatic speech recognition with a fixed bitrate budget—0
Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft's Submission to SwissText 2021—0
Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition—0
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts—0
Learning Audio-Visual DereverberationCode1
Assessing the Use of Prosody in Constituency Parsing of Imperfect TranscriptsCode0
SynthASR: Unlocking Synthetic Data for Speech Recognition—0
Cross-utterance Reranking Models with BERT and Graph Convolutional Networks for Conversational Speech Recognition—0
Incorporating External POS Tagger for Punctuation RestorationCode1
Leveraging Pre-trained Language Model for Speech Sentiment Analysis—0
Improving RNN-T ASR Performance with Date-Time and Location Awareness—0
TASK AWARE MULTI-TASK LEARNING FOR SPEECH TO TEXT TASKS—0
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition—0
Unsupervised Automatic Speech Recognition: A Review—0
A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition—0
Sequential End-to-End Intent and Slot Label Classification and Localization—0
Data Augmentation Methods for End-to-end Speech Recognition on Distant-Talk Scenarios—0
Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement—0
Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audio—0
Semantic-WER: A Unified Metric for the Evaluation of ASR Transcript for End Usability—0
Show:102550
← PrevPage 71 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