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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 1176–1200 of 3012 papers

TitleStatusHype
Exploratory Evaluation of Speech Content Masking—0
Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech—0
Exploring CTC Based End-to-End Techniques for Myanmar Speech Recognition—0
Exploring data augmentation in bias mitigation against non-native-accented speech—0
Exploring Effective Distillation of Self-Supervised Speech Models for Automatic Speech Recognition—0
Exploring Gender Disparities in Automatic Speech Recognition Technology—0
Building and Evaluation of a Real Room Impulse Response Dataset—0
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training—0
Exploring Machine Speech Chain for Domain Adaptation and Few-Shot Speaker Adaptation—0
Exploring Methods for the Automatic Detection of Errors in Manual Transcription—0
Exploring Pre-training with Alignments for RNN Transducer based End-to-End Speech Recognition—0
Exploring RNN-Transducer for Chinese Speech Recognition—0
Exploring Speech Enhancement for Low-resource Speech Synthesis—0
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition—0
Exploring SSL Discrete Tokens for Multilingual ASR—0
Exploring Targeted Universal Adversarial Perturbations to End-to-end ASR Models—0
Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation—0
Exploring the Effect of Dialect Mismatched Language Models in Telugu Automatic Speech Recognition—0
Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages—0
Exploring the Integration of E2E ASR and Pronunciation Modeling for English Mispronunciation Detection—0
Exploring the Integration of Large Language Models into Automatic Speech Recognition Systems: An Empirical Study—0
Exploring the Integration of Speech Separation and Recognition with Self-Supervised Learning Representation—0
Exploring the Role of Audio in Video Captioning—0
Exploring Transfer Learning For End-to-End Spoken Language Understanding—0
Blind Signal Dereverberation for Machine 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