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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 1251–1300 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
Environment-aware Reconfigurable Noise Suppression—0
Entity resolution for noisy ASR transcripts—0
Causal Analysis of ASR Errors for Children: Quantifying the Impact of Physiological, Cognitive, and Extrinsic Factors—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
Blockwise Streaming Transformer for Spoken Language Understanding and Simultaneous Speech Translation—0
Free English and Czech telephone speech corpus shared under the CC-BY-SA 3.0 license—0
Entity Linking for Spoken Language—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
Ensemble knowledge distillation of self-supervised speech models—0
Blind Signal Dereverberation for Machine Speech Recognition—0
From Weak Labels to Strong Results: Utilizing 5,000 Hours of Noisy Classroom Transcripts with Minimal Accurate Data—0
FT Speech: Danish Parliament Speech Corpus—0
Full-text Error Correction for Chinese Speech Recognition with Large Language Model—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
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices—0
Challenges of Computational Processing of Code-Switching—0
Fundamental Frequency Feature Normalization and Data Augmentation for Child Speech Recognition—0
Fusing ASR Outputs in Joint Training for Speech Emotion Recognition—0
Efficiently Fusing Pretrained Acoustic and Linguistic Encoders for Low-resource Speech Recognition—0
FusionFormer: Fusing Operations in Transformer for Efficient Streaming Speech Recognition—0
Fusion Models for Improved Visual Captioning—0
G2G: TTS-Driven Pronunciation Learning for Graphemic Hybrid ASR—0
Gated Recurrent Fusion with Joint Training Framework for Robust End-to-End Speech Recognition—0
G-Augment: Searching for the Meta-Structure of Data Augmentation Policies for ASR—0
Gaussian Kernelized Self-Attention for Long Sequence Data and Its Application to CTC-based Speech Recognition—0
GEC-RAG: Improving Generative Error Correction via Retrieval-Augmented Generation for Automatic Speech Recognition Systems—0
Gender and Dialect Bias in YouTube's Automatic Captions—0
Gender Representation in French Broadcast Corpora and Its Impact on ASR Performance—0
Generating diverse and natural text-to-speech samples using a quantized fine-grained VAE and auto-regressive prosody prior—0
Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model—0
Generating Robust Audio Adversarial Examples using Iterative Proportional Clipping—0
Generating Synthetic Audio Data for Attention-Based Speech Recognition Systems—0
Ensemble Chinese End-to-End Spoken Language Understanding for Abnormal Event Detection from audio stream—0
Enriching ASR Lattices with POS Tags for Dependency Parsing—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