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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 2626–2650 of 3012 papers

TitleStatusHype
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
On-Device Neural Language Model Based Word PredictionCode0
Deep Learning for Dialogue Systems—0
Structured Dialogue Policy with Graph Neural Networks—0
Neural Network Architectures for Arabic Dialect Identification—0
Code-Switching Detection with Data-Augmented Acoustic and Language Models—0
Building a Unified Code-Switching ASR System for South African Languages—0
Back-Translation-Style Data Augmentation for End-to-End ASR—0
Articulatory Features for ASR of Pathological Speech—0
Acoustic and Textual Data Augmentation for Improved ASR of Code-Switching Speech—0
A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech RecognitionCode0
Open Source Automatic Speech Recognition for GermanCode1
Automatic Speech Recognition for Humanitarian Applications in Somali—0
Zero-shot keyword spotting for visual speech recognition in-the-wildCode1
Hierarchical Multi Task Learning With CTC—0
Concept-Based Embeddings for Natural Language Processing—0
Hybrid CTC-Attention based End-to-End Speech Recognition using Subword Units—0
A Comparison of Adaptation Techniques and Recurrent Neural Network ArchitecturesCode0
Foreign English Accent Adjustment by Learning Phonetic Patterns—0
A Bilingual Interactive Human Avatar Dialogue System—0
A Unified Neural Architecture for Joint Dialog Act Segmentation and Recognition in Spoken Dialog System—0
Transliteration Better than Translation? Answering Code-mixed Questions over a Knowledge Base—0
Integrating Multiple NLP Technologies into an Open-source Platform for Multilingual Media Monitoring—0
Joint Part-of-Speech and Language ID Tagging for Code-Switched Data—0
Phone Merging For Code-Switched Speech Recognition—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