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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 2651–2675 of 3012 papers

TitleStatusHype
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling—0
An End-to-End Text-independent Speaker Verification Framework with a Keyword Adversarial Network—0
An enhanced automatic speech recognition system for Arabic—0
A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer And Large Scale Synthetic Data—0
An evaluation of word-level confidence estimation for end-to-end automatic speech recognition—0
A New Benchmark for Evaluating Automatic Speech Recognition in the Arabic Call Domain—0
An Exhaustive Evaluation of TTS- and VC-based Data Augmentation for ASR—0
An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition—0
An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting—0
An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition—0
An Improved Residual LSTM Architecture for Acoustic Modeling—0
An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition—0
An Incremental Algorithm for Transition-based CCG Parsing—0
An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples—0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition—0
An Investigation Into On-device Personalization of End-to-end Automatic Speech Recognition Models—0
An Investigation of Enhancing CTC Model for Triggered Attention-based Streaming ASR—0
An Investigation of Hybrid architectures for Low Resource Multilingual Speech Recognition system in Indian context—0
An investigation of modularity for noise robustness in conformer-based ASR—0
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition—0
An Investigation on Applying Acoustic Feature Conversion to ASR of Adult and Child Speech—0
An Investigative Study of Multi-Modal Cross-Lingual Retrieval—0
Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi—0
A Noise-Robust Self-supervised Pre-training Model Based Speech Representation Learning for Automatic Speech Recognition—0
A non-expert Kaldi recipe for Vietnamese Speech Recognition System—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