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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 2701–2725 of 3012 papers

TitleStatusHype
Artie Bias Corpus: An Open Dataset for Detecting Demographic Bias in Speech Applications—0
Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech—0
ArzEn: A Speech Corpus for Code-switched Egyptian Arabic-English—0
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection—0
A Self-Attentive Model with Gate Mechanism for Spoken Language Understanding—0
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic Speech—0
A Semi-Automated Live Interlingual Communication Workflow Featuring Intralingual Respeaking: Evaluation and Benchmarking—0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data—0
Ask2Mask: Guided Data Selection for Masked Speech Modeling—0
A Speech Test Set of Practice Business Presentations with Additional Relevant Texts—0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling—0
Automatic Speech Recognition Advancements for Indigenous Languages of the Americas—0
ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition—0
ASR-Aware End-to-end Neural Diarization—0
ASR-based CALL systems and learner speech data: new resources and opportunities for research and development in second language learning—0
ASR-based Features for Emotion Recognition: A Transfer Learning Approach—0
ASR Bundestag: A Large-Scale political debate dataset in German—0
ASR-EC Benchmark: Evaluating Large Language Models on Chinese ASR Error Correction—0
ASR Error Correction and Domain Adaptation Using Machine Translation—0
ASR Error Correction using Large Language Models—0
ASR Error Detection via Audio-Transcript entailment—0
ASR error management for improving spoken language understanding—0
ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems—0
ASR for Documenting Acutely Under-Resourced Indigenous Languages—0
ASR for Non-standardised Languages with Dialectal Variation: the case of Swiss German—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