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 13511400 of 6433 papers

TitleStatusHype
A Winograd-based Integrated Photonics Accelerator for Convolutional Neural Networks0
An Effective Mixture-Of-Experts Approach For Code-Switching Speech Recognition Leveraging Encoder Disentanglement0
A Web Service for Pre-segmenting Very Long Transcribed Speech Recordings0
A Web Application for Automated Dialect Analysis0
An Effective End-to-End Modeling Approach for Mispronunciation Detection0
A Dataset for Multimodal Question Answering in the Cultural Heritage Domain0
A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability0
A Wavelet Transform Based Scheme to Extract Speech Pitch and Formant Frequencies0
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features0
Avoid Overthinking in Self-Supervised Models for Speech Recognition0
An Effective Context-Balanced Adaptation Approach for Long-Tailed Speech Recognition0
A Comparison of Speech Data Augmentation Methods Using S3PRL Toolkit0
A Voice Controlled E-Commerce Web Application0
An Effective Automated Speaking Assessment Approach to Mitigating Data Scarcity and Imbalanced Distribution0
A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers0
Anchored Speech Recognition with Neural Transducers0
AdaScale SGD: A Scale-Invariant Algorithm for Distributed Training0
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard0
AVFormer: Injecting Vision into Frozen Speech Models for Zero-Shot AV-ASR0
Avengers, Ensemble! Benefits of ensembling in grapheme-to-phoneme prediction0
AV-data2vec: Self-supervised Learning of Audio-Visual Speech Representations with Contextualized Target Representations0
An automated medical scribe for documenting clinical encounters0
AdaPTwin: Low-Cost Adaptive Compression of Product Twins in Transformers0
A Comparison of Modeling Units in Sequence-to-Sequence Speech Recognition with the Transformer on Mandarin Chinese0
A Berkeley View of Systems Challenges for AI0
Improving OOV Detection and Resolution with External Language Models in Acoustic-to-Word ASR0
AV-CPL: Continuous Pseudo-Labeling for Audio-Visual Speech Recognition0
Avaya Conversational Intelligence: A Real-Time System for Spoken Language Understanding in Human-Human Call Center Conversations0
An Audio-enriched BERT-based Framework for Spoken Multiple-choice Question Answering0
AVATAR: Robust Voice Search Engine Leveraging Autoregressive Document Retrieval and Contrastive Learning0
An Attentional Model for Speech Translation Without Transcription0
Adaptive Sparse and Monotonic Attention for Transformer-based Automatic Speech Recognition0
A Variational EM Method for Pole-Zero Modeling of Speech with Mixed Block Sparse and Gaussian Excitation0
Anatomy of Industrial Scale Multilingual ASR0
Avanc\'ees dans le domaine de la transcription automatique par d\'ecodage guid\'e (Improvements on driven decoding system combination) [in French]0
Auxiliary Sequence Labeling Tasks for Disfluency Detection0
An ASR-free Fluency Scoring Approach with Self-Supervised Learning0
Adaptive Parser-Centric Text Normalization0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading0
Auxiliary Interference Speaker Loss for Target-Speaker Speech Recognition0
An ASR-Based Tutor for Learning to Read: How to Optimize Feedback to First Graders0
Auto-tuning TensorFlow Threading Model for CPU Backend0
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data0
An Approach to Improve Robustness of NLP Systems against ASR Errors0
Automating speech reception threshold measurements using automatic speech recognition0
An Application for Building a Polish Telephone Speech Corpus0
Automatic Viseme Vocabulary Construction to Enhance Continuous Lip-reading0
Automatic Transcription Challenges for Inuktitut, a Low-Resource Polysynthetic Language0
An analysis of incorporating an external language model into a sequence-to-sequence model0
Adaptive multilingual speech recognition with pretrained models0
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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