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 46514700 of 6433 papers

TitleStatusHype
Toward Automated Content Feedback Generation for Non-native Spontaneous Speech0
Toward Automated Detection of Biased Social Signals from the Content of Clinical Conversations0
Toward a Web-based Speech Corpus for Algerian Dialectal Arabic Varieties0
Toward Computation and Memory Efficient Neural Network Acoustic Models with Binary Weights and Activations0
Toward Cross-Domain Speech Recognition with End-to-End Models0
Toward domain-invariant speech recognition via large scale training0
Toward Fairness in AI for People with Disabilities: A Research Roadmap0
Toward Fairness in Speech Recognition: Discovery and mitigation of performance disparities0
Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions0
Toward Practical Automatic Speech Recognition and Post-Processing: a Call for Explainable Error Benchmark Guideline0
Towards Accurate Text Verbalization for ASR Based on Audio Alignment0
Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and its Applications0
Towards a Generalizable Speech Marker for Parkinson's Disease Diagnosis0
Towards a Knowledge Graph based Speech Interface0
Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations0
Towards an Automatic Assessment of Crowdsourced Data for NLU0
Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration0
Towards an Open-Source Dutch Speech Recognition System for the Healthcare Domain0
Towards a Self-Learning Assistive Vocal Interface: Vocabulary and Grammar Learning0
Towards a Semantic Annotation of English Television News - Building and Evaluating a Constraint Grammar FrameNet0
Towards a Single ASR Model That Generalizes to Disordered Speech0
MERaLiON-SpeechEncoder: Towards a Speech Foundation Model for Singapore and Beyond0
Towards ASR Robust Spoken Language Understanding Through In-Context Learning With Word Confusion Networks0
Towards a Unified ASR System for the Armenian Standards0
Towards Automated Assessment of Stuttering and Stuttering Therapy0
Towards Automated Single Channel Source Separation using Neural Networks0
Towards Automatic Data Augmentation for Disordered Speech Recognition0
Towards Automatic Transcription of ILSE ― an Interdisciplinary Longitudinal Study of Adult Development and Aging0
Towards better decoding and language model integration in sequence to sequence models0
Towards Better Meta-Initialization with Task Augmentation for Kindergarten-aged Speech Recognition0
Towards Building an Automatic Transcription System for Language Documentation: Experiences from Muyu0
Towards capturing fine phonetic variation in speech using articulatory features0
Towards Data Distillation for End-to-end Spoken Conversational Question Answering0
Towards Deep Learning-aided Wireless Channel Estimation and Channel State Information Feedback for 6G0
Towards Dog Bark Decoding: Leveraging Human Speech Processing for Automated Bark Classification0
Towards Effective and Compact Contextual Representation for Conformer Transducer Speech Recognition Systems0
Towards efficient end-to-end speech recognition with biologically-inspired neural networks0
Towards end-2-end learning for predicting behavior codes from spoken utterances in psychotherapy conversations0
Towards End-to-end Automatic Code-Switching Speech Recognition0
Towards End-to-End Code-Switching Speech Recognition0
Towards End-To-End Speech Recognition with Recurrent Neural Networks0
Towards End-to-End Spoken Grammatical Error Correction0
Towards End-to-end Unsupervised Speech Recognition0
Towards Estimating the Upper Bound of Visual-Speech Recognition: The Visual Lip-Reading Feasibility Database0
Towards Evaluating the Robustness of Automatic Speech Recognition Systems via Audio Style Transfer0
Towards Fluent Translations from Disfluent Speech0
Towards Fully Automatic Annotation of Audio Books for TTS0
Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili0
Towards High-fidelity Singing Voice Conversion with Acoustic Reference and Contrastive Predictive Coding0
Towards High-Reliability Speech Translation in the Medical Domain0
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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