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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 1376–1400 of 3012 papers

TitleStatusHype
Hybrid Autoregressive Transducer (hat)—0
Hybrid CTC-Attention based End-to-End Speech Recognition using Subword Units—0
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR—0
Hybridized Feature Extraction and Acoustic Modelling Approach for Dysarthric Speech Recognition—0
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch—0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks—0
Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks—0
An investigation of modularity for noise robustness in conformer-based ASR—0
Enhancing Multilingual ASR for Unseen Languages via Language Embedding Modeling—0
Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings—0
Advanced Long-context End-to-end Speech Recognition Using Context-expanded Transformers—0
ICMC-ASR: The ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition Challenge—0
Ideal-LLM: Integrating Dual Encoders and Language-Adapted LLM for Multilingual Speech-to-Text—0
Identifying dialects with textual and acoustic cues—0
Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts—0
Identifying Teacher Questions Using Automatic Speech Recognition in Classrooms—0
IE-CPS Lexicon: An Automatic Speech Recognition Oriented Indian-English Pronunciation Dictionary—0
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale—0
Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than Others—0
Impact of ASR on Alzheimer’s Disease Detection: All Errors are Equal, but Deletions are More Equal than Others—0
Impact of Dataset on Acoustic Models for Automatic Speech Recognition—0
Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport—0
ASR in German: A Detailed Error Analysis—0
Importance of Different Temporal Modulations of Speech: A Tale of Two Perspectives—0
Self-Supervised Learning for Multi-Channel Neural Transducer—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