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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 1501–1525 of 3012 papers

TitleStatusHype
Aligning Pre-trained Models for Spoken Language Translation—0
Aligning Speech to Languages to Enhance Code-switching Speech Recognition—0
Alignment Entropy Regularization—0
Alignment-Free Training for Transducer-based Multi-Talker ASR—0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition—0
Alignment Restricted Streaming Recurrent Neural Network Transducer—0
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework—0
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation—0
A Likelihood Ratio based Domain Adaptation Method for E2E Models—0
All-neural beamformer for continuous speech separation—0
All-neural online source separation, counting, and diarization for meeting analysis—0
Almost Unsupervised Text to Speech and Automatic Speech Recognition—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network—0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition—0
Amharic-English Speech Translation in Tourism Domain—0
A Mixture of Expert Based Deep Neural Network for Improved ASR—0
Amortized Neural Networks for Low-Latency Speech Recognition—0
AMPS: ASR with Multimodal Paraphrase Supervision—0
A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation—0
A Multimodal Approach to Device-Directed Speech Detection with Large Language Models—0
A Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answering—0
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset—0
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition—0
An Adaptive Psychoacoustic Model for Automatic Speech Recognition—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