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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 976–1000 of 3012 papers

TitleStatusHype
Dynamic Masking for Improved Stability in Spoken Language Translation—0
Acoustic Word Disambiguation with Phonogical Features in Danish ASR—0
Dyn-ASR: Compact, Multilingual Speech Recognition via Spoken Language and Accent Identification—0
Continuous Speech Recognition using EEG and Video—0
Continuous Pseudo-Labeling from the Start—0
Continuously Learning New Words in Automatic Speech Recognition—0
E-Branchformer: Branchformer with Enhanced merging for speech recognition—0
ATC-ANNO: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation—0
Echotune: A Modular Extractor Leveraging the Variable-Length Nature of Speech in ASR Tasks—0
Algorithms For Automatic Accentuation And Transcription Of Russian Texts In Speech Recognition Systems—0
EdgeCRNN: an edgecomputing oriented model of acoustic feature enhancement for keyword spotting—0
探討聲學模型的合併技術與半監督鑑別式訓練於會議語音辨識之研究 (Investigating acoustic model combination and semi-supervised discriminative training for meeting speech recognition) [In Chinese]—0
會議語音辨識使用語者資訊之語言模型調適技術 (On the Use of Speaker-Aware Language Model Adaptation Techniques for Meeting Speech Recognition ) [In Chinese]—0
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence—0
Continued Pretraining for Domain Adaptation of Wav2vec2.0 in Automatic Speech Recognition for Elementary Math Classroom Settings—0
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning—0
Effectively pretraining a speech translation decoder with Machine Translation data—0
Asynchronous Decentralized Distributed Training of Acoustic Models—0
A Lexical-aware Non-autoregressive Transformer-based ASR Model—0
Acoustic-to-articulatory Speech Inversion with Multi-task Learning—0
Effective Text Adaptation for LLM-based ASR through Soft Prompt Fine-Tuning—0
Continual learning using lattice-free MMI for speech recognition—0
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models—0
Continual Learning in Machine Speech Chain Using Gradient Episodic Memory—0
A Survey on Speech Large Language Models—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