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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 801–825 of 3012 papers

TitleStatusHype
Svarah: Evaluating English ASR Systems on Indian Accents—0
ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition—0
Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator—0
InterFormer: Interactive Local and Global Features Fusion for Automatic Speech Recognition—0
Incorporating Ultrasound Tongue Images for Audio-Visual Speech Enhancement through Knowledge Distillation—0
Iteratively Improving Speech Recognition and Voice Conversion—0
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding—0
On the Transferability of Whisper-based Representations for "In-the-Wild" Cross-Task Downstream Speech Applications—0
Evaluating OpenAI's Whisper ASR for Punctuation Prediction and Topic Modeling of life histories of the Museum of the Person—0
BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR—0
Personalized Predictive ASR for Latency Reduction in Voice Assistants—0
SE-Bridge: Speech Enhancement with Consistent Brownian Bridge—0
TranUSR: Phoneme-to-word Transcoder Based Unified Speech Representation Learning for Cross-lingual Speech Recognition—0
Text Generation with Speech Synthesis for ASR Data Augmentation—0
CopyNE: Better Contextual ASR by Copying Named EntitiesCode1
GNCformer Enhanced Self-attention for Automatic Speech Recognition—0
Semantic VAD: Low-Latency Voice Activity Detection for Speech Interaction—0
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages—0
On the Efficacy and Noise-Robustness of Jointly Learned Speech Emotion and Automatic Speech Recognition—0
Self-supervised representations in speech-based depression detection—0
Unsupervised ASR via Cross-Lingual Pseudo-Labeling—0
BAT: Boundary aware transducer for memory-efficient and low-latency ASR—0
Making More of Little Data: Improving Low-Resource Automatic Speech Recognition Using Data AugmentationCode1
A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks—0
A Lexical-aware Non-autoregressive Transformer-based ASR Model—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