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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 1501–1550 of 3012 papers

TitleStatusHype
Analysis of EEG frequency bands for Envisioned Speech RecognitionCode0
Shallow Fusion of Weighted Finite-State Transducer and Language Model for Text NormalizationCode0
Improving Generalization of Deep Neural Network Acoustic Models with Length Perturbation and N-best Based Label Smoothing—0
Short-Term Word-Learning in a Dynamically Changing Environment—0
Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems—0
Finnish Parliament ASR corpus - Analysis, benchmarks and statisticsCode0
A Dataset for Speech Emotion Recognition in Greek Theatrical PlaysCode0
A Speech Representation Anonymization Framework via Selective Noise PerturbationCode0
Speech-enhanced and Noise-aware Networks for Robust Speech RecognitionCode0
Impact of Dataset on Acoustic Models for Automatic Speech Recognition—0
Disentangleing Content and Fine-grained Prosody Information via Hybrid ASR Bottleneck Features for Voice Conversion—0
Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks—0
Computing Optimal Location of Microphone for Improved Speech Recognition—0
Pseudo Label Is Better Than Human Label—0
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis—0
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis—0
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition—0
Representative Subset Selection for Efficient Fine-Tuning in Self-Supervised Speech Recognition—0
Prediction of speech intelligibility with DNN-based performance measures—0
Whither the Priors for (Vocal) Interactivity?—0
RED-ACE: Robust Error Detection for ASR using Confidence EmbeddingsCode0
Spectral Modification Based Data Augmentation For Improving End-to-End ASR For Children's Speech—0
Transformer-based Streaming ASR with Cumulative Attention—0
Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems—0
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling—0
Which French speech recognition system for assistant robots?—0
Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition SystemsCode0
A Conformer Based Acoustic Model for Robust Automatic Speech Recognition—0
Extended Graph Temporal Classification for Multi-Speaker End-to-End ASR—0
Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training—0
Integrating Text Inputs For Training and Adapting RNN Transducer ASR Models—0
A Survey of Multilingual Models for Automatic Speech Recognition—0
Language technology practitioners as language managers: arbitrating data bias and predictive bias in ASR—0
Ask2Mask: Guided Data Selection for Masked Speech Modeling—0
Towards Better Meta-Initialization with Task Augmentation for Kindergarten-aged Speech Recognition—0
Differentially Private Speaker Anonymization—0
Korean Tokenization for Beam Search Rescoring in Speech Recognition—0
Improving CTC-based speech recognition via knowledge transferring from pre-trained language modelsCode0
VADOI:Voice-Activity-Detection Overlapping Inference For End-to-end Long-form Speech Recognition—0
Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition—0
r-G2P: Evaluating and Enhancing Robustness of Grapheme to Phoneme Conversion by Controlled noise introducing and Contextual information incorporation—0
SemEval 2022 Task 12: Symlink- Linking Mathematical Symbols to their Descriptions—0
Domain Adaptation of low-resource Target-Domain models using well-trained ASR Conformer Models—0
'Beach' to 'Bitch': Inadvertent Unsafe Transcription of Kids' Content on YouTube—0
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition—0
MLP-ASR: Sequence-length agnostic all-MLP architectures for speech recognition—0
ADIMA: Abuse Detection In Multilingual AudioCode0
Conversational Speech Recognition By Learning Conversation-level Characteristics—0
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers—0
Multi-style Training for South African Call Centre Audio—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