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 1626–1650 of 3012 papers

TitleStatusHype
Neural Network Architectures for Arabic Dialect Identification—0
Neural Network-Based Modeling of Phonetic Durations—0
Neural Network Language Modeling with Letter-based Features and Importance Sampling—0
Neural Speech Translation at AppTek—0
Neural Transducer Training: Reduced Memory Consumption with Sample-wise Computation—0
Neural Zero-Inflated Quality Estimation Model For Automatic Speech Recognition System—0
Neuro-SERKET: Development of Integrative Cognitive System through the Composition of Deep Probabilistic Generative Models—0
New Baseline in Automatic Speech Recognition for Northern S\'ami—0
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision—0
NGPU-LM: GPU-Accelerated N-Gram Language Model for Context-Biasing in Greedy ASR Decoding—0
Noise Flooding for Detecting Audio Adversarial Examples Against Automatic Speech Recognition—0
Noise Masking Attacks and Defenses for Pretrained Speech Models—0
Noise Robust IOA/CAS Speech Separation and Recognition System For The Third 'CHIME' Challenge—0
Noisy Training Improves E2E ASR for the Edge—0
Non-Autoregressive Chinese ASR Error Correction with Phonological Training—0
Non-autoregressive End-to-end Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding—0
Non-Autoregressive Transformer ASR with CTC-Enhanced Decoder Input—0
Listen and Fill in the Missing Letters: Non-Autoregressive Transformer for Speech Recognition—0
Non-autoregressive Transformer-based End-to-end ASR using BERT—0
Non-autoregressive Transformer with Unified Bidirectional Decoder for Automatic Speech Recognition—0
Non-intrusive speech intelligibility prediction using automatic speech recognition derived measures—0
Non-Parallel Voice Conversion for ASR Augmentation—0
Nonparametric Bayesian Double Articulation Analyzer for Direct Language Acquisition from Continuous Speech Signals—0
NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speech—0
No Pitch Left Behind: Addressing Gender Unbalance in Automatic Speech Recognition through Pitch Manipulation—0
Show:102550
← PrevPage 66 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