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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 1626–1650 of 3012 papers

TitleStatusHype
Lattention: Lattice-attention in ASR rescoring—0
A Conformer-based ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement and Speech Separation—0
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions—0
Attention-based Multi-hypothesis Fusion for Speech SummarizationCode0
Speech-to-SQL Parsing: Error Correction with Multi-modal Representations—0
On Spoken Language Understanding Systems for Low Resourced Languages—0
Two Front-Ends, One Model : Fusing Heterogeneous Speech Features for Low Resource ASR with Multilingual Pre-Training—0
Improving Multimodal Speech Recognition by Data Augmentation and Speech Representations—0
Heterogeneous Language Model Optimization in Automatic Speech Recognition—0
Progressive Down-Sampling for Acoustic Encoding—0
A Novel End-to-End CAPT System for L2 Children Learners—0
Who Are We Talking About? Handling Person Names in Speech Translation—0
Attention based end to end Speech Recognition for Voice Search in Hindi and English—0
Prediction of Listener Perception of Argumentative Speech in a Crowdsourced Dataset Using (Psycho-)Linguistic and Fluency Features—0
Self-Normalized Importance Sampling for Neural Language Modeling—0
Scaling ASR Improves Zero and Few Shot Learning—0
Privacy attacks for automatic speech recognition acoustic models in a federated learning framework—0
Conformer-based Hybrid ASR System for Switchboard Dataset—0
Context-Aware Transformer Transducer for Speech Recognition—0
Effective Cross-Utterance Language Modeling for Conversational Speech Recognition—0
Sequential Randomized Smoothing for Adversarially Robust Speech RecognitionCode0
Speech recognition for air traffic control via feature learning and end-to-end training—0
A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding—0
STC speaker recognition systems for the NIST SRE 2021—0
Recent Advances in End-to-End Automatic Speech Recognition—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