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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2001–2025 of 3012 papers

TitleStatusHype
Speech Recognition by Simply Fine-tuning BERT—0
BCN2BRNO: ASR System Fusion for Albayzin 2020 Speech to Text Challenge—0
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yoloxóchitl Mixtec—0
Streaming Models for Joint Speech Recognition and Translation—0
Exploiting Beam Search Confidence for Energy-Efficient Speech Recognition—0
Arabic Speech Recognition by End-to-End, Modular Systems and HumanCode0
Efficiently Fusing Pretrained Acoustic and Linguistic Encoders for Low-resource Speech Recognition—0
An evaluation of word-level confidence estimation for end-to-end automatic speech recognition—0
Fast offline Transformer-based end-to-end automatic speech recognition for real-world applications—0
WER-BERT: Automatic WER Estimation with BERT in a Balanced Ordinal Classification Paradigm—0
Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings—0
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition—0
Why Does Decentralized Training Outperform Synchronous Training In The Large Batch Setting?—0
Learning without Forgetting: Task Aware Multitask Learning for Multi-Modality Tasks—0
Multi-channel Multi-frame ADL-MVDR for Target Speech Separation—0
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews—0
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition—0
Adjust-free adversarial example generation in speech recognition using evolutionary multi-objective optimization under black-box condition—0
Toward Streaming ASR with Non-Autoregressive Insertion-based Model—0
User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis—0
Exploring Transfer Learning For End-to-End Spoken Language Understanding—0
A review of on-device fully neural end-to-end automatic speech recognition algorithms—0
Less Is More: Improved RNN-T Decoding Using Limited Label Context and Path Merging—0
Improved Robustness to Disfluencies in RNN-Transducer Based Speech Recognition—0
On Knowledge Distillation for Direct Speech Translation—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