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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 1001–1025 of 3012 papers

TitleStatusHype
Biased Self-supervised learning for ASR—0
Leveraging Domain Features for Detecting Adversarial Attacks Against Deep Speech Recognition in Noise—0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks—0
Streaming Audio-Visual Speech Recognition with Alignment Regularization—0
Phonetic-assisted Multi-Target Units Modeling for Improving Conformer-Transducer ASR system—0
Probing Statistical Representations For End-To-End ASR—0
Monolingual Recognizers Fusion for Code-switching Speech Recognition—0
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech ProcessingCode1
More Speaking or More Speakers?—0
InterMPL: Momentum Pseudo-Labeling with Intermediate CTC Loss—0
Towards Zero-Shot Code-Switched Speech Recognition—0
BECTRA: Transducer-based End-to-End ASR with BERT-Enhanced Encoder—0
data2vec-aqc: Search for the right Teaching Assistant in the Teacher-Student training setupCode1
A Preliminary Study on Automated Speaking Assessment of English as a Second Language (ESL) Students—0
Mandarin-English Code-Switching Speech Recognition System for Specific Domain—0
Unified End-to-End Speech Recognition and Endpointing for Fast and Efficient Speech Systems—0
Adapting self-supervised models to multi-talker speech recognition using speaker embeddings—0
A Comparative Study on Multichannel Speaker-Attributed Automatic Speech Recognition in Multi-party Meetings—0
FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition—0
An analysis of degenerating speech due to progressive dysarthria on ASR performance—0
DiaCorrect: End-to-end error correction for speaker diarizationCode0
Delay-penalized transducer for low-latency streaming ASRCode3
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings—0
Predicting Multi-Codebook Vector Quantization Indexes for Knowledge Distillation—0
Blank Collapse: Compressing CTC emission for the faster decodingCode0
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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