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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 376–400 of 3012 papers

TitleStatusHype
AMPS: ASR with Multimodal Paraphrase Supervision—0
Adaptable End-to-End ASR Models using Replaceable Internal LMs and Residual Softmax—0
Amortized Neural Networks for Low-Latency Speech Recognition—0
AdaMER-CTC: Connectionist Temporal Classification with Adaptive Maximum Entropy Regularization for Automatic Speech Recognition—0
4-bit Quantization of LSTM-based Speech Recognition Models—0
Handling Numeric Expressions in Automatic Speech Recognition—0
Improving OOV Detection and Resolution with External Language Models in Acoustic-to-Word ASR—0
Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies—0
A Mixture of Expert Based Deep Neural Network for Improved ASR—0
Amharic-English Speech Translation in Tourism Domain—0
Adam^+: A Stochastic Method with Adaptive Variance Reduction—0
ADAGIO: Interactive Experimentation with Adversarial Attack and Defense for Audio—0
A meta learning scheme for fast accent domain expansion in Mandarin speech recognition—0
A Code-Switching Corpus of Turkish-German Conversations—0
On the Problem of Text-To-Speech Model Selection for Synthetic Data Generation in Automatic Speech Recognition—0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network—0
Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses—0
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications—0
Almost Unsupervised Text to Speech and Automatic Speech Recognition—0
All-neural online source separation, counting, and diarization for meeting analysis—0
AC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup—0
Listening while Speaking and Visualizing: Improving ASR through Multimodal Chain—0
A Universally-Deployable ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement, and Voice Separation—0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition—0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications—0
Show:102550
← PrevPage 16 of 121Next →
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