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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

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Showing 501–525 of 3012 papers

TitleStatusHype
BART based semantic correction for Mandarin automatic speech recognition system—0
BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR—0
Blind Signal Dereverberation for Machine Speech Recognition—0
BAT: Boundary aware transducer for memory-efficient and low-latency ASR—0
Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words—0
Bayesian Learning of LF-MMI Trained Time Delay Neural Networks for Speech Recognition—0
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction—0
BayesSpeech: A Bayesian Transformer Network for Automatic Speech Recognition—0
Attention-based Wav2Text with Feature Transfer Learning—0
BCN2BRNO: ASR System Fusion for Albayzin 2020 Speech to Text Challenge—0
Attention based on-device streaming speech recognition with large speech corpus—0
Alignment Restricted Streaming Recurrent Neural Network Transducer—0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition—0
Attention based end to end Speech Recognition for Voice Search in Hindi and English—0
A CTC Triggered Siamese Network with Spatial-Temporal Dropout for Speech Recognition—0
3-D Feature and Acoustic Modeling for Far-Field Speech Recognition—0
Alignment-Free Training for Transducer-based Multi-Talker ASR—0
Attention-based ASR with Lightweight and Dynamic Convolutions—0
Alignment Entropy Regularization—0
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition—0
A CLARIN Transcription Portal for Interview Data—0
Blind and neural network-guided convolutional beamformer for joint denoising, dereverberation, and source separation—0
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation—0
Boosting End-to-End Multilingual Phoneme Recognition through Exploiting Universal Speech Attributes Constraints—0
Bootstrap an end-to-end ASR system by multilingual training, transfer learning, text-to-text mapping and synthetic audio—0
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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