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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 1176–1200 of 3012 papers

TitleStatusHype
Challenges of Computational Processing of Code-Switching—0
Challenges of Applying Automatic Speech Recognition for Transcribing EU Parliament Committee Meetings: A Pilot Study—0
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection—0
Affect Recognition in Conversations Using Large Language Models—0
A Corpus for Modeling Word Importance in Spoken Dialogue Transcripts—0
Accented Speech Recognition Inspired by Human Perception—0
Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio—0
Towards Better Understanding of Spontaneous Conversations: Overcoming Automatic Speech Recognition Errors With Intent Recognition—0
Challenges in Speech Recognition and Translation of High-Value Low-Density Polysynthetic Languages—0
Challenges and Opportunities of Speech Recognition for Bengali Language—0
Challenges and Opportunities in Multi-device Speech Processing—0
Chain-of-Thought Prompting for Speech Translation—0
ArzEn: A Speech Corpus for Code-switched Egyptian Arabic-English—0
Advocating Character Error Rate for Multilingual ASR Evaluation—0
Chain of Correction for Full-text Speech Recognition with Large Language Models—0
CEASR: A Corpus for Evaluating Automatic Speech Recognition—0
A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting—0
Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech—0
Adversarial Training of End-to-end Speech Recognition Using a Criticizing Language Model—0
A Corpus and Phonetic Dictionary for Tunisian Arabic Speech Recognition—0
Causal Structure Discovery for Error Diagnostics of Children's ASR—0
Causal Analysis of ASR Errors for Children: Quantifying the Impact of Physiological, Cognitive, and Extrinsic Factors—0
Artie Bias Corpus: An Open Dataset for Detecting Demographic Bias in Speech Applications—0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface—0
Articulatory Features for ASR of Pathological Speech—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