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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 2151–2175 of 3012 papers

TitleStatusHype
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
Iterative Compression of End-to-End ASR Model using AutoML—0
Unsupervised Cross-Domain Singing Voice Conversion—0
Weakly Supervised Construction of ASR Systems with Massive Video Data—0
"This is Houston. Say again, please". The Behavox system for the Apollo-11 Fearless Steps Challenge (phase II)—0
Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones—0
Modular End-to-end Automatic Speech Recognition Framework for Acoustic-to-word Model—0
Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability—0
Exploiting Cross-Lingual Knowledge in Unsupervised Acoustic Modeling for Low-Resource Languages—0
Neural Kalman Filtering for Speech Enhancement—0
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models—0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition—0
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks—0
Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations—0
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems—0
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters—0
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition—0
Robust Prediction of Punctuation and Truecasing for Medical ASR—0
How Accents Confound: Probing for Accent Information in End-to-End Speech Recognition Systems—0
Towards Stream Translation: Adaptive Computation Time for Simultaneous Machine Translation—0
Robust Neural Machine Translation with ASR Errors—0
Towards Understanding ASR Error Correction for Medical Conversations—0
Multimodal and Multiresolution Speech Recognition with Transformers—0
CUNI Neural ASR with Phoneme-Level Intermediate Step for -Native at IWSLT 2020—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—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