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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 901–950 of 3012 papers

TitleStatusHype
UML: A Universal Monolingual Output Layer for Multilingual ASR—0
MADI: Inter-domain Matching and Intra-domain Discrimination for Cross-domain Speech Recognition—0
Improving Contextual Spelling Correction by External Acoustics Attention and Semantic Aware Data Augmentation—0
Gradient Remedy for Multi-Task Learning in End-to-End Noise-Robust Speech RecognitionCode1
Connecting Humanities and Social Sciences: Applying Language and Speech Technology to Online Panel Surveys—0
An ASR-free Fluency Scoring Approach with Self-Supervised Learning—0
Emphasizing Unseen Words: New Vocabulary Acquisition for End-to-End Speech Recognition—0
A Sidecar Separator Can Convert a Single-Talker Speech Recognition System to a Multi-Talker OneCode1
Speaker and Language Change Detection using Wav2vec2 and Whisper—0
Massively Multilingual Shallow Fusion with Large Language Models—0
Stabilising and accelerating light gated recurrent units for automatic speech recognition—0
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition—0
Speaker Change Detection for Transformer Transducer ASR—0
Adaptable End-to-End ASR Models using Replaceable Internal LMs and Residual Softmax—0
Confidence Score Based Speaker Adaptation of Conformer Speech Recognition SystemsCode0
ASR Bundestag: A Large-Scale political debate dataset in German—0
ASDF: A Differential Testing Framework for Automatic Speech Recognition SystemsCode0
PATCorrect: Non-autoregressive Phoneme-augmented Transformer for ASR Error Correction—0
Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions—0
MAC: A unified framework boosting low resource automatic speech recognition—0
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech RecognitionCode1
Improving Rare Words Recognition through Homophone Extension and Unified Writing for Low-resource Cantonese Speech Recognition—0
Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives—0
Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case StudyCode0
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset—0
Language Agnostic Data-Driven Inverse Text Normalization—0
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition—0
Syllable Subword Tokens for Open Vocabulary Speech Recognition in MalayalamCode0
BayesSpeech: A Bayesian Transformer Network for Automatic Speech Recognition—0
Multi-resolution location-based training for multi-channel continuous speech separation—0
Using Kaldi for Automatic Speech Recognition of Conversational Austrian German—0
Streaming Punctuation: A Novel Punctuation Technique Leveraging Bidirectional Context for Continuous Speech Recognition—0
Audio-Visual Efficient Conformer for Robust Speech RecognitionCode1
Towards Voice Reconstruction from EEG during Imagined SpeechCode1
Memory Augmented Lookup Dictionary based Language Modeling for Automatic Speech Recognition—0
Don't Be So Sure! Boosting ASR Decoding via Confidence Relaxation—0
Skit-S2I: An Indian Accented Speech to Intent datasetCode1
Alignment Entropy Regularization—0
End-to-End Automatic Speech Recognition model for the Sudanese Dialect—0
4D ASR: Joint modeling of CTC, Attention, Transducer, and Mask-Predict decoders—0
Mu^2SLAM: Multitask, Multilingual Speech and Language Models—0
NusaCrowd: Open Source Initiative for Indonesian NLP ResourcesCode2
Fast Entropy-Based Methods of Word-Level Confidence Estimation for End-To-End Automatic Speech Recognition—0
Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasksCode0
Context-aware Fine-tuning of Self-supervised Speech Models—0
Speech Aware Dialog System Technology Challenge (DSTC11)—0
BLASER: A Text-Free Speech-to-Speech Translation Evaluation MetricCode2
Improving Fast-slow Encoder based Transducer with Streaming Deliberation—0
Disentangling Prosody Representations with Unsupervised Speech Reconstruction—0
Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator—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