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

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Showing 5201–5250 of 6433 papers

TitleStatusHype
A bandit approach to curriculum generation for automatic speech recognition—0
A baseline model for computationally inexpensive speech recognition for Kazakh using the Coqui STT framework—0
A Bayesian Approach to Estimation of Speaker Normalization Parameters—0
A Bayesian Approach to Recurrence in Neural Networks—0
A Bayesian Network View on Acoustic Model-Based Techniques for Robust Speech Recognition—0
A belief tracking challenge task for spoken dialog systems—0
A Benchmark of French ASR Systems Based on Error Severity—0
A Berkeley View of Systems Challenges for AI—0
A Bilingual Interactive Human Avatar Dialogue System—0
A brief history of AI: how to prevent another winter (a critical review)—0
A Broadcast News Corpus for Evaluation and Tuning of German LVCSR Systems—0
Abstractive Meeting Summarization with Entailment and Fusion—0
A Case Study on Combining ASR and Visual Features for Generating Instructional Video Captions—0
A case study on using speech-to-translation alignments for language documentation—0
A Causal Inference Approach for Quantifying Research Impact—0
Accelerating CNN inference on FPGAs: A Survey—0
Accelerating Minibatch Stochastic Gradient Descent using Typicality Sampling—0
Accelerating recurrent neural network language model based online speech recognition system—0
Accelerating Transducers through Adjacent Token Merging—0
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices—0
Accelerator-Aware Training for Transducer-Based Speech Recognition—0
Accent Adaptation for the Air Traffic Control Domain—0
AccentDB: A Database of Non-Native English Accents to Assist Neural Speech Recognition—0
Accented Speech Recognition: A Survey—0
Accented Speech Recognition: Benchmarking, Pre-training, and Diverse Data—0
Accented Speech Recognition Inspired by Human Perception—0
AccentFold: A Journey through African Accents for Zero-Shot ASR Adaptation to Target Accents—0
Accent Recognition with Hybrid Phonetic Features—0
Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings—0
Accurate and Reliable Confidence Estimation Based on Non-Autoregressive End-to-End Speech Recognition System—0
Accurate and Structured Pruning for Efficient Automatic Speech Recognition—0
Accurate synthesis of Dysarthric Speech for ASR data augmentation—0
A Challenge Set for Advancing Language Modeling—0
Achieving Human Parity in Conversational Speech Recognition—0
A CLARIN Transcription Portal for Interview Data—0
A Closer Look at Audio-Visual Multi-Person Speech Recognition and Active Speaker Selection—0
A Closer Look at Wav2Vec2 Embeddings for On-Device Single-Channel Speech Enhancement—0
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers—0
AC-Mix: Self-Supervised Adaptation for Low-Resource Automatic Speech Recognition using Agnostic Contrastive Mixup—0
A Coarse-Grained Model for Optimal Coupling of ASR and SMT Systems for Speech Translation—0
A Code-Switching Corpus of Turkish-German Conversations—0
A collaborative filtering model with heterogeneous neural networks for recommender systems—0
A comparable study of modeling units for end-to-end Mandarin speech recognition—0
A Comparative Analysis of Bilingual and Trilingual Wav2Vec Models for Automatic Speech Recognition in Multilingual Oral History Archives—0
A Comparative Analysis of Crowdsourced Natural Language Corpora for Spoken Dialog Systems—0
A Comparative Study of Extremely Low-Resource Transliteration of the World's Languages—0
A Comparative Study of LLM-based ASR and Whisper in Low Resource and Code Switching Scenario—0
A Comparative Study of Methods for Topic Modeling in Spoken Document Retrieval—0
A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio—0
A Comparative Study of Reinforcement Learning Techniques on Dialogue Management—0
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All datasetsLibriSpeech test-cleanLibriSpeech test-otherSwitchboard + Hub500TIMITAISHELL-1WSJ eval92Common Voice Germanswb_hub_500 WER fullSWBCHTUDACommon Voice FrenchCommon Voice SpanishMediaSpeech

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AmNetWord Error Rate (WER)8.6—Unverified
2HMM-(SAT)GMMWord Error Rate (WER)8—Unverified
3Local Prior Matching (Large Model)Word Error Rate (WER)7.19—Unverified
4SnipsWord Error Rate (WER)6.4—Unverified
5Li-GRUWord Error Rate (WER)6.2—Unverified
6HMM-DNN + pNorm*Word Error Rate (WER)5.5—Unverified
7CTC + policy learningWord Error Rate (WER)5.42—Unverified
8Deep Speech 2Word Error Rate (WER)5.33—Unverified
9HMM-TDNN + iVectorsWord Error Rate (WER)4.8—Unverified
10Gated ConvNetsWord Error Rate (WER)4.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Local Prior Matching (Large Model)Word Error Rate (WER)20.84—Unverified
2SnipsWord Error Rate (WER)16.5—Unverified
3Local Prior Matching (Large Model, ConvLM LM)Word Error Rate (WER)15.28—Unverified
4Deep Speech 2Word Error Rate (WER)13.25—Unverified
5TDNN + pNorm + speed up/down speechWord Error Rate (WER)12.5—Unverified
6CTC-CRF 4gram-LMWord Error Rate (WER)10.65—Unverified
7Convolutional Speech RecognitionWord Error Rate (WER)10.47—Unverified
8MT4SSLWord Error Rate (WER)9.6—Unverified
9Jasper DR 10x5Word Error Rate (WER)8.79—Unverified
10EspressoWord Error Rate (WER)8.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Deep SpeechPercentage error20—Unverified
2DNN-HMMPercentage error18.5—Unverified
3CD-DNNPercentage error16.1—Unverified
4DNNPercentage error16—Unverified
5DNN + DropoutPercentage error15—Unverified
6DNN BMMIPercentage error12.9—Unverified
7DNN MPEPercentage error12.9—Unverified
8DNN MMIPercentage error12.9—Unverified
9HMM-TDNN + pNorm + speed up/down speechPercentage error12.9—Unverified
10HMM-DNN +sMBRPercentage error12.6—Unverified
#ModelMetricClaimedVerifiedStatus
1LSNNPercentage error33.2—Unverified
2LAS multitask with indicators samplingPercentage error20.4—Unverified
3Soft Monotonic Attention (ours, offline)Percentage error20.1—Unverified
4QCNN-10L-256FMPercentage error19.64—Unverified
5Bi-LSTM + skip connections w/ CTCPercentage error17.7—Unverified
6Bi-RNN + AttentionPercentage error17.6—Unverified
7RNN-CRF on 24(x3) MFSCPercentage error17.3—Unverified
8CNN in time and frequency + dropout, 17.6% w/o dropoutPercentage error16.7—Unverified
9Light Gated Recurrent UnitsPercentage error16.7—Unverified
10GRUPercentage error16.6—Unverified
#ModelMetricClaimedVerifiedStatus
1AttWord Error Rate (WER)18.7—Unverified
2CTC/AttWord Error Rate (WER)6.7—Unverified
3BRA-EWord Error Rate (WER)6.63—Unverified
4CTC-CRF 4gram-LMWord Error Rate (WER)6.34—Unverified
5BATWord Error Rate (WER)4.97—Unverified
6ParaformerWord Error Rate (WER)4.95—Unverified
7U2Word Error Rate (WER)4.72—Unverified
8UMAWord Error Rate (WER)4.7—Unverified
9Lightweight TransducerWord Error Rate (WER)4.31—Unverified
10CIF-HKD With LMWord Error Rate (WER)4.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Jasper 10x3Word Error Rate (WER)6.9—Unverified
2CNN over RAW speech (wav)Word Error Rate (WER)5.6—Unverified
3CTC-CRF 4gram-LMWord Error Rate (WER)3.79—Unverified
4Deep Speech 2Word Error Rate (WER)3.6—Unverified
5test-set on open vocabulary (i.e. harder), model = HMM-DNN + pNorm*Word Error Rate (WER)3.6—Unverified
6Convolutional Speech RecognitionWord Error Rate (WER)3.5—Unverified
7TC-DNN-BLSTM-DNNWord Error Rate (WER)3.5—Unverified
8EspressoWord Error Rate (WER)3.4—Unverified
9CTC-CRF VGG-BLSTMWord Error Rate (WER)3.2—Unverified
10Transformer with Relaxed AttentionWord Error Rate (WER)3.19—Unverified