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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 651–675 of 3012 papers

TitleStatusHype
Massive End-to-end Models for Short Search Queries—0
Affect Recognition in Conversations Using Large Language Models—0
Big model only for hard audios: Sample dependent Whisper model selection for efficient inferencesCode0
Memory-augmented conformer for improved end-to-end long-form ASRCode1
Sparsely Shared LoRA on Whisper for Child Speech Recognition—0
Leveraging Data Collection and Unsupervised Learning for Code-switched Tunisian Arabic Automatic Speech Recognition—0
Exploring Speech Enhancement for Low-resource Speech Synthesis—0
Incorporating Ultrasound Tongue Images for Audio-Visual Speech Enhancement—0
Harnessing the Zero-Shot Power of Instruction-Tuned Large Language Model in End-to-End Speech Recognition—0
Semi-Autoregressive Streaming ASR With Label Context—0
HTEC: Human Transcription Error Correction—0
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models—0
HypR: A comprehensive study for ASR hypothesis revising with a reference corpusCode1
Investigating End-to-End ASR Architectures for Long Form Audio Transcription—0
Training dynamic models using early exits for automatic speech recognition on resource-constrained devicesCode0
Instruction-Following Speech Recognition—0
A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting—0
Enhancing Quantised End-to-End ASR Models via PersonalisationCode0
Improving Speech Recognition for African American English With Audio Classification—0
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation—0
Boosting End-to-End Multilingual Phoneme Recognition through Exploiting Universal Speech Attributes Constraints—0
Transformer Based Punctuation Restoration for TurkishCode0
t-SOT FNT: Streaming Multi-talker ASR with Text-only Domain Adaptation Capability—0
Combining TF-GridNet and Mixture Encoder for Continuous Speech Separation for Meeting Transcription—0
Towards Word-Level End-to-End Neural Speaker Diarization with Auxiliary Network—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