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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 951–975 of 3012 papers

TitleStatusHype
Don't Be So Sure! Boosting ASR Decoding via Confidence Relaxation—0
Don't Stop Self-Supervision: Accent Adaptation of Speech Representations via Residual Adapters—0
Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?—0
Do You Listen with One or Two Microphones? A Unified ASR Model for Single and Multi-Channel Audio—0
DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR—0
Driving ROVER with Segment-based ASR Quality Estimation—0
An Investigation of End-to-End Multichannel Speech Recognition for Reverberant and Mismatch Conditions—0
Dual Causal/Non-Causal Self-Attention for Streaming End-to-End Speech Recognition—0
On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR—0
Algorithms For Automatic Accentuation And Transcription Of Russian Texts In Speech Recognition Systems—0
Dual Language Models for Code Switched Speech Recognition—0
Continuous Learning for Children's ASR: Overcoming Catastrophic Forgetting with Elastic Weight Consolidation and Synaptic Intelligence—0
Dual Script E2E framework for Multilingual and Code-Switching ASR—0
DUAL: Textless Spoken Question Answering with Speech Discrete Unit Adaptive Learning—0
Continued Pretraining for Domain Adaptation of Wav2vec2.0 in Automatic Speech Recognition for Elementary Math Classroom Settings—0
DualVC 3: Leveraging Language Model Generated Pseudo Context for End-to-end Low Latency Streaming Voice Conversion—0
DualVoice: Speech Interaction that Discriminates between Normal and Whispered Voice Input—0
DuDe: Dual-Decoder Multilingual ASR for Indian Languages using Common Label Set—0
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning—0
DuTongChuan: Context-aware Translation Model for Simultaneous Interpreting—0
Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition—0
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model—0
Dynamic Context-Aware Streaming Pretrained Language Model For Inverse Text Normalization—0
Dynamic Data Pruning for Automatic Speech Recognition—0
Asynchronous Decentralized Distributed Training of Acoustic 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