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 15011550 of 6433 papers

TitleStatusHype
Convolutional Attention-based Seq2Seq Neural Network for End-to-End ASR0
CoALT: A Software for Comparing Automatic Labelling Tools0
A Survey on Spoken Italian Datasets and Corpora0
A language score based output selection method for multilingual speech recognition0
Convolutional Neural Networks for Speech Controlled Prosthetic Hands0
Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting0
A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search0
Convolutional Variational Autoencoders for Spectrogram Compression in Automatic Speech Recognition0
Convo: What does conversational programming need? An exploration of machine learning interface design0
ConvRNN-T: Convolutional Augmented Recurrent Neural Network Transducers for Streaming Speech Recognition0
Conv-Transformer Transducer: Low Latency, Low Frame Rate, Streamable End-to-End Speech Recognition0
CNVSRC 2024: The Second Chinese Continuous Visual Speech Recognition Challenge0
CNVSRC 2023: The First Chinese Continuous Visual Speech Recognition Challenge0
CORDIC Is All You Need0
CORILGA: a Galician Multilevel Annotated Speech Corpus for Linguistic Analysis0
Corpora for Cross-Language Information Retrieval in Six Less-Resourced Languages0
Corpus Development of Kiswahili Speech Recognition Test and Evaluation sets, Preemptively Mitigating Demographic Bias Through Collaboration with Linguists0
Corpus Generation for Voice Command in Smart Home and the Effect of Speech Synthesis on End-to-End SLU0
A Review of Meta-Reinforcement Learning for Deep Neural Networks Architecture Search0
Corpus Synthesis for Zero-shot ASR domain Adaptation using Large Language Models0
Correction Focused Language Model Training for Speech Recognition0
Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model0
CorrectSpeech: A Fully Automated System for Speech Correction and Accent Reduction0
Correlated Bigram LSA for Unsupervised Language Model Adaptation0
A Fast-Converged Acoustic Modeling for Korean Speech Recognition: A Preliminary Study on Time Delay Neural Network0
COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learning0
CoSTA: Code-Switched Speech Translation using Aligned Speech-Text Interleaving0
AccentFold: A Journey through African Accents for Zero-Shot ASR Adaptation to Target Accents0
CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments0
CoT-ST: Enhancing LLM-based Speech Translation with Multimodal Chain-of-Thought0
Could a Computer Architect Understand our Brain?0
Counting What Counts: Decompounding for Keyphrase Extraction0
A Text Normalisation System for Non-Standard English Words0
Coupling Knowledge-Based and Data-Driven Systems for Named Entity Recognition0
CNN architecture extraction on edge GPU0
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing0
CPJD Corpus: Crowdsourced Parallel Speech Corpus of Japanese Dialects0
CPPF: A contextual and post-processing-free model for automatic speech recognition0
CMU’s IWSLT 2022 Dialect Speech Translation System0
Learning Speech Representation From Contrastive Token-Acoustic Pretraining0
CPT-Boosted Wav2vec2.0: Towards Noise Robust Speech Recognition for Classroom Environments0
CR-CTC: Consistency regularization on CTC for improved speech recognition0
Creating Lithuanian and Latvian Speech Corpora from Inaccurately Annotated Web Data0
Aligner-Encoders: Self-Attention Transformers Can Be Self-Transducers0
Creating Spoken Dialog Systems in Ultra-Low Resourced Settings0
CRF-based Single-stage Acoustic Modeling with CTC Topology0
A Review of Deep Learning Techniques for Speech Processing0
Critical Appraisal of Artificial Intelligence-Mediated Communication0
A Dynamic Programming Algorithm for Computing N-gram Posteriors from Lattices0
Community Detection Clustering via Gumbel Softmax0
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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
9Gated ConvNetsWord Error Rate (WER)4.8Unverified
10HMM-TDNN + iVectorsWord 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
7HMM-TDNN + pNorm + speed up/down speechPercentage error12.9Unverified
8DNN MPEPercentage error12.9Unverified
9DNN MMIPercentage error12.9Unverified
10CNN + Bi-RNN + CTC (speech to letters), 25.9% WER if trainedonlyon SWBPercentage 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
6TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5Unverified
7Convolutional Speech RecognitionWord 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