SOTAVerified

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

Showing 16011625 of 3012 papers

TitleStatusHype
Arabic Code-Switching Speech Recognition using Monolingual Data0
Arabic Language WEKA-Based Dialect Classifier for Arabic Automatic Speech Recognition Transcripts0
A Recorded Debating Dataset0
Are disentangled representations all you need to build speaker anonymization systems?0
Are Transformers in Pre-trained LM A Good ASR Encoder? An Empirical Study0
A review of on-device fully neural end-to-end automatic speech recognition algorithms0
Articulatory and bottleneck features for speaker-independent ASR of dysarthric speech0
Articulatory Features for ASR of Pathological Speech0
Artie Bias Corpus: An Open Dataset for Detecting Demographic Bias in Speech Applications0
Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech0
ArzEn: A Speech Corpus for Code-switched Egyptian Arabic-English0
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection0
A Self-Attentive Model with Gate Mechanism for Spoken Language Understanding0
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic Speech0
A Semi-Automated Live Interlingual Communication Workflow Featuring Intralingual Respeaking: Evaluation and Benchmarking0
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data0
Ask2Mask: Guided Data Selection for Masked Speech Modeling0
A Speech Test Set of Practice Business Presentations with Additional Relevant Texts0
ASR Adaptation for E-commerce Chatbots using Cross-Utterance Context and Multi-Task Language Modeling0
Automatic Speech Recognition Advancements for Indigenous Languages of the Americas0
ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition0
ASR-Aware End-to-end Neural Diarization0
ASR-based CALL systems and learner speech data: new resources and opportunities for research and development in second language learning0
ASR-based Features for Emotion Recognition: A Transfer Learning Approach0
ASR Bundestag: A Large-Scale political debate dataset in German0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1Unverified
2TM-seq2seqTest WER9.7Unverified
3CTC/attentionTest WER8.2Unverified
4LF-MMI TDNNTest WER6.7Unverified
5Whisper-LLaMATest WER6.6Unverified
6End2end ConformerTest WER3.9Unverified
7End2end ConformerTest WER3.7Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7Unverified
9CTC/AttentionTest WER1.5Unverified
10WhisperTest WER1.3Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5Unverified
2CleanMel-L-maskCER14.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32Unverified
2Whisper-largev3-finetunedTest WER10.82Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98Unverified