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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 2576–2600 of 3012 papers

TitleStatusHype
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks—0
A Generative Model of a Pronunciation Lexicon for Hindi—0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking—0
Agent-Aware Dropout DQN for Safe and Efficient On-line Dialogue Policy Learning—0
A Hardware-Oriented and Memory-Efficient Method for CTC Decoding—0
A Hierarchical Neural Model for Learning Sequences of Dialogue Acts—0
A Hierarchical Reasoning Graph Neural Network for The Automatic Scoring of Answer Transcriptions in Video Job Interviews—0
A higher order Minkowski loss for improved prediction ability of acoustic model in ASR—0
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition—0
Ain't Misbehavin' -- Using LLMs to Generate Expressive Robot Behavior in Conversations with the Tabletop Robot Haru—0
Bonseyes AI Pipeline -- bringing AI to you. End-to-end integration of data, algorithms and deployment tools—0
A Joint Model of Orthography and Morphological Segmentation—0
A Language Agnostic Multilingual Streaming On-Device ASR System—0
A Lexical-aware Non-autoregressive Transformer-based ASR Model—0
Algorithms For Automatic Accentuation And Transcription Of Russian Texts In Speech Recognition Systems—0
A light-weight and efficient punctuation and word casing prediction model for on-device streaming ASR—0
A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems—0
Aligning Pre-trained Models for Spoken Language Translation—0
Aligning Speech to Languages to Enhance Code-switching Speech Recognition—0
Alignment Entropy Regularization—0
Alignment-Free Training for Transducer-based Multi-Talker ASR—0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition—0
Alignment Restricted Streaming Recurrent Neural Network Transducer—0
Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework—0
Align, Write, Re-order: Explainable End-to-End Speech Translation via Operation Sequence Generation—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