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 24012425 of 3012 papers

TitleStatusHype
WEST: Word Encoded Sequence Transducers0
What is lost in Normalization? Exploring Pitfalls in Multilingual ASR Model Evaluations0
When CTC Training Meets Acoustic Landmarks0
When End-to-End is Overkill: Rethinking Cascaded Speech-to-Text Translation0
Where are we in Named Entity Recognition from Speech?0
Where are we in semantic concept extraction for Spoken Language Understanding?0
Which French speech recognition system for assistant robots?0
Whisper Finetuning on Nepali Language0
Whispering in Amharic: Fine-tuning Whisper for Low-resource Language0
Whispering in Norwegian: Navigating Orthographic and Dialectic Challenges0
WhisperKit: On-device Real-time ASR with Billion-Scale Transformers0
Whither the Priors for (Vocal) Interactivity?0
Who Are We Talking About? Handling Person Names in Speech Translation0
Who Are We Talking About? Handling Person Names in Speech Translation0
Who Needs Decoders? Efficient Estimation of Sequence-level Attributes0
Why Does Decentralized Training Outperform Synchronous Training In The Large Batch Setting?0
Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customization0
Without Further Ado: Direct and Simultaneous Speech Translation by AppTek in 20210
WNARS: WFST based Non-autoregressive Streaming End-to-End Speech Recognition0
Word-Free Spoken Language Understanding for Mandarin-Chinese0
Word-level confidence estimation for RNN transducers0
Word Order Does Not Matter For Speech Recognition0
Words Worth: Verbal Content and Hirability Impressions in YouTube Video Resumes0
Word Transduction for Addressing the OOV Problem in Machine Translation for Similar Resource-Scarce Languages0
XLS-R Deep Learning Model for Multilingual ASR on Low- Resource Languages: Indonesian, Javanese, and Sundanese0
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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