SOTAVerified

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 1401–1450 of 3012 papers

TitleStatusHype
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition—0
Blending LLMs into Cascaded Speech Translation: KIT's Offline Speech Translation System for IWSLT 2024—0
Improved Conformer-based End-to-End Speech Recognition Using Neural Architecture Search—0
Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing—0
Improved Contextual Recognition In Automatic Speech Recognition Systems By Semantic Lattice Rescoring—0
Improved far-field speech recognition using Joint Variational Autoencoder—0
An investigation of modularity for noise robustness in conformer-based ASR—0
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training—0
Improved Mask-CTC for Non-Autoregressive End-to-End ASR—0
Enhancing Multilingual ASR for Unseen Languages via Language Embedding Modeling—0
Improved Robustness to Disfluencies in RNN-Transducer Based Speech Recognition—0
Improved Self-Supervised Multilingual Speech Representation Learning Combined with Auxiliary Language Information—0
Improved Speech Pre-Training with Supervision-Enhanced Acoustic Unit—0
Improved Training Techniques for Online Neural Machine Translation—0
Improved Transcription and Indexing of Oral History Interviews for Digital Humanities Research—0
Improve Sinhala Speech Recognition Through e2e LF-MMI Model—0
Advanced Long-context End-to-end Speech Recognition Using Context-expanded Transformers—0
Improving Accented Speech Recognition with Multi-Domain Training—0
Improving Accent Identification and Accented Speech Recognition Under a Framework of Self-supervised Learning—0
Improving accuracy of rare words for RNN-Transducer through unigram shallow fusion—0
Improving ASR Contextual Biasing with Guided Attention—0
Confusion2Vec: Towards Enriching Vector Space Word Representations with Representational Ambiguities—0
Self-Supervised Learning for Multi-Channel Neural Transducer—0
Improving Black-box Speech Recognition using Semantic Parsing—0
Improving callsign recognition with air-surveillance data in air-traffic communication—0
Improving Character Error Rate Is Not Equal to Having Clean Speech: Speech Enhancement for ASR Systems with Black-box Acoustic Models—0
Improving Code-switched ASR with Linguistic Information—0
Improving Code-Switching and Named Entity Recognition in ASR with Speech Editing based Data Augmentation—0
Improving Neural Biasing for Contextual Speech Recognition by Early Context Injection and Text Perturbation—0
Improving Confidence Estimation on Out-of-Domain Data for End-to-End Speech Recognition—0
Improving Contextual Spelling Correction by External Acoustics Attention and Semantic Aware Data Augmentation—0
Improving Cross-Lingual Transfer Learning for End-to-End Speech Recognition with Speech Translation—0
Improving CTC-AED model with integrated-CTC and auxiliary loss regularization—0
Improving CTC-based ASR Models with Gated Interlayer Collaboration—0
Construction of a Large-scale Japanese ASR Corpus on TV Recordings—0
Improving Data Driven Inverse Text Normalization using Data Augmentation—0
Improving Distinction between ASR Errors and Speech Disfluencies with Feature Space Interpolation—0
Improving Dysarthric Speech Intelligibility Using Cycle-consistent Adversarial Training—0
Improving EEG based Continuous Speech Recognition—0
Improving End-to-End Bangla Speech Recognition with Semi-supervised Training—0
Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis—0
Improving End-to-end Speech Recognition with Pronunciation-assisted Sub-word Modeling—0
Enhancing Lyrics Transcription on Music Mixtures with Consistency Loss—0
Improving Fast-slow Encoder based Transducer with Streaming Deliberation—0
Improving Frame-level Classifier for Word Timings with Non-peaky CTC in End-to-End Automatic Speech Recognition—0
Improving Generalization of Deep Neural Network Acoustic Models with Length Perturbation and N-best Based Label Smoothing—0
Improving Hybrid CTC/Attention End-to-end Speech Recognition with Pretrained Acoustic and Language Model—0
Improving Hypernasality Estimation with Automatic Speech Recognition in Cleft Palate Speech—0
Enhancing Low-Resource ASR through Versatile TTS: Bridging the Data Gap—0
An Investigation of Hybrid architectures for Low Resource Multilingual Speech Recognition system in Indian context—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