SOTAVerified

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

Showing 15511575 of 3012 papers

TitleStatusHype
An Effective End-to-End Modeling Approach for Mispronunciation Detection0
An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement0
An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcripts0
An Effective Training Framework for Light-Weight Automatic Speech Recognition Models0
An Efficient and Effective Online Sentence Segmenter for Simultaneous Interpretation0
An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems0
An efficient text augmentation approach for contextualized Mandarin speech recognition0
An Empirical Study of Automatic Chinese Word Segmentation for Spoken Language Understanding and Named Entity Recognition0
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling0
An End-to-End Text-independent Speaker Verification Framework with a Keyword Adversarial Network0
An enhanced automatic speech recognition system for Arabic0
A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer And Large Scale Synthetic Data0
An evaluation of word-level confidence estimation for end-to-end automatic speech recognition0
A New Benchmark for Evaluating Automatic Speech Recognition in the Arabic Call Domain0
An Exhaustive Evaluation of TTS- and VC-based Data Augmentation for ASR0
An Experimental Study on Private Aggregation of Teacher Ensemble Learning for End-to-End Speech Recognition0
An Experiment on Speech-to-Text Translation Systems for Manipuri to English on Low Resource Setting0
An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition0
An Improved Residual LSTM Architecture for Acoustic Modeling0
An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition0
An Incremental Algorithm for Transition-based CCG Parsing0
An Integrated Algorithm for Robust and Imperceptible Audio Adversarial Examples0
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition0
An Investigation Into On-device Personalization of End-to-end Automatic Speech Recognition Models0
An Investigation of Enhancing CTC Model for Triggered Attention-based Streaming ASR0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1Unverified
2TM-seq2seqTest WER9.7Unverified
3CTC/attentionTest WER8.2Unverified
4LF-MMI TDNNTest WER6.7Unverified
5Whisper-LLaMATest WER6.6Unverified
6End2end ConformerTest WER3.9Unverified
7End2end ConformerTest WER3.7Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7Unverified
9CTC/AttentionTest WER1.5Unverified
10WhisperTest WER1.3Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5Unverified
2CleanMel-L-maskCER14.4Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32Unverified
2Whisper-largev3-finetunedTest WER10.82Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98Unverified