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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 1151–1200 of 3012 papers

TitleStatusHype
E-PUR: An Energy-Efficient Processing Unit for Recurrent Neural Networks—0
BLSTM-Based Confidence Estimation for End-to-End Speech Recognition—0
Evaluation of Off-the-shelf Speech Recognizers on Different Accents in a Dialogue Domain—0
Evaluation of real-time transcriptions using end-to-end ASR models—0
Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data—0
Everything Can Be Described in Words: A Simple Unified Multi-Modal Framework with Semantic and Temporal Alignment—0
Evolutionary optimization of contexts for phonetic correction in speech recognition systems—0
An Investigative Study of Multi-Modal Cross-Lingual Retrieval—0
Environment-aware Reconfigurable Noise Suppression—0
Entity resolution for noisy ASR transcripts—0
Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition—0
Exploiting Beam Search Confidence for Energy-Efficient Speech Recognition—0
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition—0
Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition—0
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation—0
Exploiting Cross-Lingual Speaker and Phonetic Diversity for Unsupervised Subword Modeling—0
Exploiting Nontrivial Connectivity for Automatic Speech Recognition—0
Exploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech—0
Exploiting semi-supervised training through a dropout regularization in end-to-end speech recognition—0
Exploiting Sentence and Context Representations in Deep Neural Models for Spoken Language Understanding—0
Entity Linking for Spoken Language—0
Exploiting the large-scale German Broadcast Corpus to boost the Fraunhofer IAIS Speech Recognition System—0
Exploration of Adapter for Noise Robust Automatic Speech Recognition—0
Exploration of End-to-End ASR for OpenSTT -- Russian Open Speech-to-Text Dataset—0
Ensemble knowledge distillation of self-supervised speech models—0
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