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 376400 of 3012 papers

TitleStatusHype
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech RecognitionCode0
Hybrid phonetic-neural model for correction in speech recognition systemsCode0
Improving the Inclusivity of Dutch Speech Recognition by Fine-tuning Whisper on the JASMIN-CGN CorpusCode0
HYBRIDFORMER: improving SqueezeFormer with hybrid attention and NSR mechanismCode0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
How Phonotactics Affect Multilingual and Zero-shot ASR PerformanceCode0
How You Say It Matters: Measuring the Impact of Verbal Disfluency Tags on Automated Dementia DetectionCode0
HuBERT-EE: Early Exiting HuBERT for Efficient Speech RecognitionCode0
Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of SpeechCode0
Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations GenerationCode0
Guided Source Separation Meets a Strong ASR Backend: Hitachi/Paderborn University Joint Investigation for Dinner Party ASRCode0
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptationCode0
Attention-based Multi-hypothesis Fusion for Speech SummarizationCode0
Graph Neural Networks for Contextual ASR with the Tree-Constrained Pointer GeneratorCode0
Guiding Frame-Level CTC Alignments Using Self-knowledge DistillationCode0
Human Transcription Quality ImprovementCode0
Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech RecognitionCode0
AI-Generated Song Detection via Lyrics TranscriptsCode0
Attentively Embracing Noise for Robust Latent Representation in BERTCode0
A Simplified Fully Quantized Transformer for End-to-end Speech RecognitionCode0
Assessing the Use of Prosody in Constituency Parsing of Imperfect TranscriptsCode0
Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative StudyCode0
Fine-Grained Grounding for Multimodal Speech RecognitionCode0
Finnish Parliament ASR corpus - Analysis, benchmarks and statisticsCode0
FLEURS: Few-shot Learning Evaluation of Universal Representations of SpeechCode0
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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