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

Showing 451475 of 3012 papers

TitleStatusHype
Automatic Speech Recognition: A Shifted Role in Early Speech Intervention?0
Automatic Speech Recognition (ASR) for the Diagnosis of pronunciation of Speech Sound Disorders in Korean children0
Attentive listening system with backchanneling, response generation and flexible turn-taking0
Automatic Speech Recognition Biases in Newcastle English: an Error Analysis0
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset0
Automatic Speech Recognition Errors as a Predictor of L2 Listening Difficulties0
Automatic Speech Recognition for African Low-Resource Languages: Challenges and Future Directions0
Automatic Speech Recognition for Biomedical Data in Bengali Language0
Automatic Speech Recognition for Hindi0
Automatic Speech Recognition for Humanitarian Applications in Somali0
Automatic Speech Recognition for Irish: the ABAIR-ÉIST System0
Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model0
Automatic Speech Recognition for Non-Native English: Accuracy and Disfluency Handling0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms0
Automatic Speech Recognition for the Ika Language0
Attentive Adversarial Learning for Domain-Invariant Training0
Automatic Speech Recognition for Uyghur through Multilingual Acoustic Modeling0
Automatic Speech Recognition in German: A Detailed Error Analysis0
Attention Enhanced Citrinet for Speech Recognition0
Automatic speech recognition in the diagnosis of primary progressive aphasia0
Automatic Speech Recognition of African American English: Lexical and Contextual Effects0
Automatic Speech Recognition of Low-Resource Languages Based on Chukchi0
Automatic Speech Recognition on a Firefighter TETRA Broadcast Channel0
Automatic Speech Recognition System-Independent Word Error Rate Estimation0
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework0
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Benchmark Results

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