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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 401–450 of 3012 papers

TitleStatusHype
All-neural online source separation, counting, and diarization for meeting analysis—0
AC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup—0
Audio De-identification - a New Entity Recognition Task—0
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance—0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network—0
Automatic Speech Recognition of Low-Resource Languages Based on Chukchi—0
Audio-visual Multi-channel Integration and Recognition of Overlapped Speech—0
Audio-visual Multi-channel Recognition of Overlapped Speech—0
Audio-visual multi-channel speech separation, dereverberation and recognition—0
Audio-visual Recognition of Overlapped speech for the LRS2 dataset—0
Automatic Speech Recognition System-Independent Word Error Rate Estimation—0
Amharic-English Speech Translation in Tourism Domain—0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings—0
Audio-Visual Speech Recognition is Worth 32328 Voxels—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture—0
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition—0
Augmenting Automatic Speech Recognition Models with Disfluency Detection—0
Augmenting Bottleneck Features of Deep Neural Network Employing Motor State for Speech Recognition at Humanoid Robots—0
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework—0
A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation—0
A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes—0
A Unified Neural Architecture for Joint Dialog Act Segmentation and Recognition in Spoken Dialog System—0
A Multimodal Approach to Device-Directed Speech Detection with Large Language Models—0
A Unified Transformer-based Framework for Duplex Text Normalization—0
A Universally-Deployable ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement, and Voice Separation—0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition—0
A two-step approach to leverage contextual data: speech recognition in air-traffic communications—0
Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies—0
Automated scoring across different modalities—0
Automated speech tools for helping communities process restricted-access corpora for language revival efforts—0
Automated speech-unit delimitation in spoken learner English—0
Automatically Assess Children's Reading Skills—0
Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics—0
Automatic assessment of spoken language proficiency of non-native children—0
Automatic Detection of Code-switching Style from Acoustics—0
All-neural beamformer for continuous speech separation—0
Automatic Documentation of ICD Codes with Far-Field Speech Recognition—0
A two-stage transliteration approach to improve performance of a multilingual ASR—0
Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish—0
Automatic Learning of Subword Dependent Model Scales—0
Automatic Quality Estimation for ASR System Combination—0
Automatic recognition and detection of aphasic natural speech—0
Automatic recognition of child speech for robotic applications in noisy environments—0
Automatic recognition of element classes and boundaries in the birdsong with variable sequences—0
Automatic recognition of suprasegmentals in speech—0
A Likelihood Ratio based Domain Adaptation Method for E2E Models—0
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition—0
Analyzing ASR pretraining for low-resource speech-to-text translation—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