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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 1251–1275 of 3012 papers

TitleStatusHype
Cascade RNN-Transducer: Syllable Based Streaming On-device Mandarin Speech Recognition with a Syllable-to-Character Converter—0
Fine-Tuning Automatic Speech Recognition for People with Parkinson's: An Effective Strategy for Enhancing Speech Technology Accessibility—0
Fine-tuning pre-trained models for Automatic Speech Recognition, experiments on a fieldwork corpus of Japhug (Trans-Himalayan family)—0
Articulatory and bottleneck features for speaker-independent ASR of dysarthric speech—0
Fine-Tuning Whisper for Inclusive Prosodic Stress Analysis—0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface—0
Blind Signal Dereverberation for Machine Speech Recognition—0
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech—0
A Complementary Joint Training Approach Using Unpaired Speech and Text for Low-Resource Automatic Speech Recognition—0
Flexible Multichannel Speech Enhancement for Noise-Robust Frontend—0
Flexi-Transducer: Optimizing Latency, Accuracy and Compute forMulti-Domain On-Device Scenarios—0
FluentNet: End-to-End Detection of Speech Disfluency with Deep Learning—0
Focused Discriminative Training For Streaming CTC-Trained Automatic Speech Recognition Models—0
Foreign English Accent Adjustment by Learning Phonetic Patterns—0
Ensemble Chinese End-to-End Spoken Language Understanding for Abnormal Event Detection from audio stream—0
Free English and Czech telephone speech corpus shared under the CC-BY-SA 3.0 license—0
Enriching ASR Lattices with POS Tags for Dependency Parsing—0
Frequency Domain Multi-channel Acoustic Modeling for Distant Speech Recognition—0
From Audio to Semantics: Approaches to end-to-end spoken language understanding—0
From English to More Languages: Parameter-Efficient Model Reprogramming for Cross-Lingual Speech Recognition—0
From Human Language Technology to Human Language Science—0
From Senones to Chenones: Tied Context-Dependent Graphemes for Hybrid Speech Recognition—0
From Statistical Methods to Pre-Trained Models; A Survey on Automatic Speech Recognition for Resource Scarce Urdu Language—0
Blind and neural network-guided convolutional beamformer for joint denoising, dereverberation, and source separation—0
Enhancing Unsupervised Speech Recognition with Diffusion GANs—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