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 21512200 of 3012 papers

TitleStatusHype
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition0
Iterative Compression of End-to-End ASR Model using AutoML0
Unsupervised Cross-Domain Singing Voice Conversion0
Weakly Supervised Construction of ASR Systems with Massive Video Data0
"This is Houston. Say again, please". The Behavox system for the Apollo-11 Fearless Steps Challenge (phase II)0
Utterance-Wise Meeting Transcription System Using Asynchronous Distributed Microphones0
Modular End-to-end Automatic Speech Recognition Framework for Acoustic-to-word Model0
Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability0
Exploiting Cross-Lingual Knowledge in Unsupervised Acoustic Modeling for Low-Resource Languages0
Neural Kalman Filtering for Speech Enhancement0
Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models0
Audio Adversarial Examples for Robust Hybrid CTC/Attention Speech Recognition0
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks0
Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations0
SoK: The Faults in our ASRs: An Overview of Attacks against Automatic Speech Recognition and Speaker Identification Systems0
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters0
Deep Graph Random Process for Relational-Thinking-Based Speech Recognition0
Robust Prediction of Punctuation and Truecasing for Medical ASR0
How Accents Confound: Probing for Accent Information in End-to-End Speech Recognition Systems0
Towards Stream Translation: Adaptive Computation Time for Simultaneous Machine Translation0
Robust Neural Machine Translation with ASR Errors0
Towards Understanding ASR Error Correction for Medical Conversations0
Multimodal and Multiresolution Speech Recognition with Transformers0
CUNI Neural ASR with Phoneme-Level Intermediate Step for -Native at IWSLT 20200
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University0
The AFRL IWSLT 2020 Systems: Work-From-Home Edition0
SimulSpeech: End-to-End Simultaneous Speech to Text Translation0
Investigating the effect of auxiliary objectives for the automated grading of learner English speech transcriptions0
Large Vocabulary Read Speech Corpora for Four Ethiopian Languages: Amharic, Tigrigna, Oromo, and Wolaytta0
End-to-End Offline Speech Translation System for IWSLT 2020 using Modality Agnostic Meta-Learning0
Towards end-2-end learning for predicting behavior codes from spoken utterances in psychotherapy conversations0
Tigrinya Automatic Speech recognition with Morpheme based recognition units0
Multi-view Frequency LSTM: An Efficient Frontend for Automatic Speech Recognition0
Neural Machine Translation for Multilingual Grapheme-to-Phoneme Conversion0
Streaming Transformer ASR with Blockwise Synchronous Inference0
Boosting Active Learning for Speech Recognition with Noisy Pseudo-labeled Samples0
Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of Any Number of Speakers0
End-to-End Code Switching Language Models for Automatic Speech Recognition0
Quantization of Acoustic Model Parameters in Automatic Speech Recognition Framework0
Towards Automated Assessment of Stuttering and Stuttering Therapy0
Exploration of End-to-End ASR for OpenSTT -- Russian Open Speech-to-Text Dataset0
The JHU Multi-Microphone Multi-Speaker ASR System for the CHiME-6 Challenge0
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification TasksCode0
Data Augmentation for Training Dialog Models Robust to Speech Recognition Errors0
Improving Cross-Lingual Transfer Learning for End-to-End Speech Recognition with Speech Translation0
Learning not to Discriminate: Task Agnostic Learning for Improving Monolingual and Code-switched Speech Recognition0
On the Effectiveness of Neural Text Generation based Data Augmentation for Recognition of Morphologically Rich Speech0
Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR0
Contextual RNN-T For Open Domain ASR0
Transfer Learning for British Sign Language Modelling0
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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