SOTAVerified

Speech Recognition

Speech Recognition is the task of converting spoken language into text. It involves recognizing the words spoken in an audio recording and transcribing them into a written format. The goal is to accurately transcribe the speech in real-time or from recorded audio, taking into account factors such as accents, speaking speed, and background noise.

( Image credit: SpecAugment )

Papers

Showing 30513100 of 6433 papers

TitleStatusHype
Enhancing Child Vocalization Classification with Phonetically-Tuned Embeddings for Assisting Autism Diagnosis0
Improving the Robustness of Speech Translation0
Improving the Training Recipe for a Robust Conformer-based Hybrid Model0
Improving Transducer-Based Spoken Language Understanding with Self-Conditioned CTC and Knowledge Transfer0
Breaking Through the Spike: Spike Window Decoding for Accelerated and Precise Automatic Speech Recognition0
Enhancing Aviation Communication Transcription: Fine-Tuning Distil-Whisper with LoRA0
Enhancing Audiovisual Speech Recognition through Bifocal Preference Optimization0
Improving Uyghur ASR systems with decoders using morpheme-based language models0
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages0
An online sequence-to-sequence model for noisy speech recognition0
Enhancing ASR for Stuttered Speech with Limited Data Using Detect and Pass0
Improving Whisper's Recognition Performance for Under-Represented Language Kazakh Leveraging Unpaired Speech and Text0
Improving Zero-Shot Chinese-English Code-Switching ASR with kNN-CTC and Gated Monolingual Datastores0
Enhancing AAC Software for Dysarthric Speakers in e-Health Settings: An Evaluation Using TORGO0
IMS-Speech: A Speech to Text Tool0
IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task0
IMS’ Systems for the IWSLT 2021 Low-Resource Speech Translation Task0
Inappropriate Pause Detection In Dysarthric Speech Using Large-Scale Speech Recognition0
Inclusive ASR for Disfluent Speech: Cascaded Large-Scale Self-Supervised Learning with Targeted Fine-Tuning and Data Augmentation0
Inclusivity of AI Speech in Healthcare: A Decade Look Back0
In-context Language Learning for Endangered Languages in Speech Recognition0
In-Context Learning Boosts Speech Recognition via Human-like Adaptation to Speakers and Language Varieties0
Breaking the Data Barrier: Towards Robust Speech Translation via Adversarial Stability Training0
Incorporating End-to-End Speech Recognition Models for Sentiment Analysis0
Enhancements in statistical spoken language translation by de-normalization of ASR results0
Incorporating L2 Phonemes Using Articulatory Features for Robust Speech Recognition0
Incorporating Language Level Information into Acoustic Models0
Incorporating Side Information into Recurrent Neural Network Language Models0
Enhancement of Dysarthric Speech Reconstruction by Contrastive Learning0
Incorporating Ultrasound Tongue Images for Audio-Visual Speech Enhancement through Knowledge Distillation0
Incorporating Ultrasound Tongue Images for Audio-Visual Speech Enhancement0
Increasing the Accessibility of Time-Aligned Speech Corpora with Spokes Mix0
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models0
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models0
Incremental Adaptation Strategies for Neural Network Language Models0
Incremental Derivations in CCG0
Incremental Dialogue Management: Survey, Discussion, and Implications for HRI0
Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device0
Incremental Learning for End-to-End Automatic Speech Recognition0
Incremental LSTM-based Dialog State Tracker0
Incremental Machine Speech Chain Towards Enabling Listening while Speaking in Real-time0
Incremental Neo-Davidsonian semantic construction for TAG0
RNN based Incremental Online Spoken Language Understanding0
Incremental Predictive Parsing with TurboParser0
BRDS: An FPGA-based LSTM Accelerator with Row-Balanced Dual-Ratio Sparsification0
Incremental Tree Substitution Grammar for Parsing and Sentence Prediction0
Critical Appraisal of Artificial Intelligence-Mediated Communication0
Independent language modeling architecture for end-to-end ASR0
Advanced Framework for Animal Sound Classification With Features Optimization0
Advanced Clustering Techniques for Speech Signal Enhancement: A Review and Metanalysis of Fuzzy C-Means, K-Means, and Kernel Fuzzy C-Means Methods0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19Unverified
4SnipsWord Error Rate (WER)6.4Unverified
5Li-GRUWord Error Rate (WER)6.2Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5Unverified
7CTC + policy learningWord Error Rate (WER)5.42Unverified
8Deep Speech 2Word Error Rate (WER)5.33Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8Unverified
10Gated ConvNetsWord Error Rate (WER)4.8Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84Unverified
2SnipsWord Error Rate (WER)16.5Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28Unverified
4Deep Speech 2Word Error Rate (WER)13.25Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47Unverified
8MT4SSLWord Error Rate (WER)9.6Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79Unverified
10EspressoWord Error Rate (WER)8.7Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20Unverified
2DNN-HMMPercentage error18.5Unverified
3CD-DNNPercentage error16.1Unverified
4DNNPercentage error16Unverified
5DNN + DropoutPercentage error15Unverified
6DNN BMMIPercentage error12.9Unverified
7DNN MPEPercentage error12.9Unverified
8DNN MMIPercentage error12.9Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
10HMM-DNN +sMBRPercentage error12.6Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2Unverified
2LAS multitask with indicators samplingPercentage error20.4Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1Unverified
4QCNN-10L-256FMPercentage error19.64Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7Unverified
6Bi-RNN + AttentionPercentage error17.6Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7Unverified
9Light Gated Recurrent UnitsPercentage error16.7Unverified
10GRUPercentage error16.6Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7Unverified
2CTC/AttWord Error Rate (WER)6.7Unverified
3BRA-EWord Error Rate (WER)6.63Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34Unverified
5BATWord Error Rate (WER)4.97Unverified
6ParaformerWord Error Rate (WER)4.95Unverified
7U2Word Error Rate (WER)4.72Unverified
8UMAWord Error Rate (WER)4.7Unverified
9Lightweight TransducerWord Error Rate (WER)4.31Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79Unverified
4Deep Speech 2Word Error Rate (WER)3.6Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
8EspressoWord Error Rate (WER)3.4Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19Unverified