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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 801–825 of 3012 papers

TitleStatusHype
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings—0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition—0
Bigger is not Always Better: The Effect of Context Size on Speech Pre-TrainingCode0
End-to-End Speech-to-Text Translation: A Survey—0
End-to-end Joint Punctuated and Normalized ASR with a Limited Amount of Punctuated Training Data—0
A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature ExtractorsCode0
How does end-to-end speech recognition training impact speech enhancement artifacts?—0
Label-Synchronous Neural Transducer for Adaptable Online E2E Speech Recognition—0
ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding—0
Improving Large-scale Deep Biasing with Phoneme Features and Text-only Data in Streaming Transducer—0
Multi-channel Conversational Speaker Separation via Neural Diarization—0
Retrieve and Copy: Scaling ASR Personalization to Large Catalogs—0
On the Effectiveness of ASR Representations in Real-world Noisy Speech Emotion Recognition—0
1SPU: 1-step Speech Processing Unit—0
A comparative analysis between Conformer-Transducer, Whisper, and wav2vec2 for improving the child speech recognitionCode0
Pseudo-Labeling for Domain-Agnostic Bangla Automatic Speech RecognitionCode0
COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning—0
Server-side Rescoring of Spoken Entity-centric Knowledge Queries for Virtual Assistants—0
RIR-SF: Room Impulse Response Based Spatial Feature for Target Speech Recognition in Multi-Channel Multi-Speaker Scenarios—0
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European LanguagesCode0
Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation—0
Conversational Speech Recognition by Learning Audio-textual Cross-modal Contextual Representation—0
Intelligibility prediction with a pretrained noise-robust automatic speech recognition model—0
Unintended Memorization in Large ASR Models, and How to Mitigate It—0
Generative error correction for code-switching speech recognition using large language models—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