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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 2601–2625 of 3012 papers

TitleStatusHype
A Likelihood Ratio based Domain Adaptation Method for E2E Models—0
All-neural beamformer for continuous speech separation—0
All-neural online source separation, counting, and diarization for meeting analysis—0
Almost Unsupervised Text to Speech and Automatic Speech Recognition—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network—0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition—0
Amharic-English Speech Translation in Tourism Domain—0
A Mixture of Expert Based Deep Neural Network for Improved ASR—0
Amortized Neural Networks for Low-Latency Speech Recognition—0
AMPS: ASR with Multimodal Paraphrase Supervision—0
A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation—0
A Multimodal Approach to Device-Directed Speech Detection with Large Language Models—0
A Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answering—0
A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset—0
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition—0
An Adaptive Psychoacoustic Model for Automatic Speech Recognition—0
Analyse de l'effet de la r\'everb\'eration sur la reconnaissance automatique de la parole (Analyzing how reverberation affects Automatic Speech Recognition)—0
Analysis of GlobalPhone and Ethiopian Languages Speech Corpora for Multilingual ASR—0
An Analysis of Semantically-Aligned Speech-Text Embeddings—0
Analysis of Manipuri Tones in ManiTo: A Tonal Contrast Database—0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—0
Analysis of Phonetic Transcription for Danish Automatic Speech Recognition—0
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition—0
Analyzing ASR pretraining for low-resource speech-to-text translation—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