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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
Private Language Model Adaptation for Speech Recognition—0
Factorized Neural Transducer for Efficient Language Model AdaptationCode1
BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition—0
Fast-MD: Fast Multi-Decoder End-to-End Speech Translation with Non-Autoregressive Hidden IntermediatesCode3
Challenges and Opportunities of Speech Recognition for Bengali Language—0
Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts—0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation—0
iRNN: Integer-only Recurrent Neural Network—0
Audio-Visual Speech Recognition is Worth 32328 Voxels—0
MeetDot: Videoconferencing with Live Translation Captions—0
Model-Based Approach for Measuring the Fairness in ASR—0
Multimodal Audio-textual Architecture for Robust Spoken Language Understanding—0
PDAugment: Data Augmentation by Pitch and Duration Adjustments for Automatic Lyrics Transcription—0
Utterance-level neural confidence measure for end-to-end children speech recognition—0
Improving Accent Identification and Accented Speech Recognition Under a Framework of Self-supervised Learning—0
Improving Streaming Transformer Based ASR Under a Framework of Self-supervised Learning—0
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech—0
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech RecognitionCode1
Non-autoregressive Transformer with Unified Bidirectional Decoder for Automatic Speech Recognition—0
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search DegradationCode0
Unsupervised Domain Adaptation Schemes for Building ASR in Low-resource Languages—0
Remember the context! ASR slot error correction through memorization—0
Self-Attention Channel Combinator Frontend for End-to-End Multichannel Far-field Speech Recognition—0
Coarse-To-Fine And Cross-Lingual ASR Transfer—0
Vietnamese end-to-end speech recognition using wav2vec 2.0Code1
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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