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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 626–650 of 3012 papers

TitleStatusHype
A privacy-preserving method using secret key for convolutional neural network-based speech classification—0
An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples—0
LibriSpeech-PC: Benchmark for Evaluation of Punctuation and Capitalization Capabilities of end-to-end ASR ModelsCode2
UniverSLU: Universal Spoken Language Understanding for Diverse Tasks with Natural Language Instructions—0
One model to rule them all ? Towards End-to-End Joint Speaker Diarization and Speech Recognition—0
AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR—0
Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping—0
The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections through Federated Learning—0
Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm—0
AV-CPL: Continuous Pseudo-Labeling for Audio-Visual Speech Recognition—0
Enhancing Code-switching Speech Recognition with Interactive Language Biases—0
SSHR: Leveraging Self-supervised Hierarchical Representations for Multilingual Automatic Speech Recognition—0
Wiki-En-ASR-Adapt: Large-scale synthetic dataset for English ASR Customization—0
Hierarchical Cross-Modality Knowledge Transfer with Sinkhorn Attention for CTC-based ASR—0
HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language ModelsCode1
Speech collage: code-switched audio generation by collaging monolingual corporaCode1
Learning from Flawed Data: Weakly Supervised Automatic Speech Recognition—0
Segmentation-Free Streaming Machine TranslationCode0
Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference—0
Connecting Speech Encoder and Large Language Model for ASR—0
Cross-modal Alignment with Optimal Transport for CTC-based ASR—0
Human Transcription Quality ImprovementCode0
Speech enhancement with frequency domain auto-regressive modeling—0
Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR—0
Affect Recognition in Conversations Using Large Language Models—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