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 601650 of 6433 papers

TitleStatusHype
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech RecognitionCode1
Computer-Generated Music for Tabletop Role-Playing GamesCode1
Can We Read Speech Beyond the Lips? Rethinking RoI Selection for Deep Visual Speech RecognitionCode1
NICE: Noise Injection and Clamping Estimation for Neural Network QuantizationCode1
Non-Attentive Tacotron: Robust and Controllable Neural TTS Synthesis Including Unsupervised Duration ModelingCode1
Language Models with Image Descriptors are Strong Few-Shot Video-Language LearnersCode1
ASR2K: Speech Recognition for Around 2000 Languages without AudioCode1
ArTST: Arabic Text and Speech TransformerCode1
Online Neural Networks for Change-Point DetectionCode1
BERTphone: Phonetically-Aware Encoder Representations for Utterance-Level Speaker and Language RecognitionCode1
On Word Error Rate Definitions and their Efficient Computation for Multi-Speaker Speech Recognition SystemsCode1
Continuous speech separation: dataset and analysisCode1
Contrastive Learning-Based Audio to Lyrics Alignment for Multiple LanguagesCode1
Controlling Whisper: Universal Acoustic Adversarial Attacks to Control Speech Foundation ModelsCode1
A transfer learning based approach for pronunciation scoringCode1
CopyNE: Better Contextual ASR by Copying Named EntitiesCode1
Personalized Autonomous Driving with Large Language Models: Field ExperimentsCode1
Learning Multi-modal Representations by Watching Hundreds of Surgical Video LecturesCode1
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERTCode1
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN ExecutionCode1
Monotonic Chunkwise AttentionCode1
Cross Attention Augmented Transducer Networks for Simultaneous TranslationCode1
Recent improvements of ASR models in the face of adversarial attacksCode1
Streaming Speaker-Attributed ASR with Token-Level Speaker EmbeddingsCode1
CTC-synchronous Training for Monotonic Attention ModelCode1
Arabic Speech Emotion Recognition Employing Wav2vec2.0 and HuBERT Based on BAVED DatasetCode1
DARF: A data-reduced FADE version for simulations of speech recognition thresholds with real hearing aidsCode1
KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube VideosCode0
Kurdish (Sorani) Speech to Text: Presenting an Experimental DatasetCode0
Keyphrase Cloud Generation of Broadcast NewsCode0
Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic InformationCode0
Key Frame Mechanism For Efficient Conformer Based End-to-end Speech RecognitionCode0
An End-to-End Neural Network for Polyphonic Piano Music TranscriptionCode0
A Deep Dive into the Disparity of Word Error Rates Across Thousands of NPTEL MOOC VideosCode0
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task LearningCode0
Jasper: An End-to-End Convolutional Neural Acoustic ModelCode0
Joint Automatic Speech Recognition And Structure Learning For Better Speech UnderstandingCode0
Iterative Pseudo-Labeling for Speech RecognitionCode0
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptationCode0
Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with AphasiaCode0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Investigating the Emergent Audio Classification Ability of ASR Foundation ModelsCode0
Intrinsic evaluation of language models for code-switchingCode0
A Comparison of Techniques for Language Model Integration in Encoder-Decoder Speech RecognitionCode0
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech RecognitionCode0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
An Effective Transformer-based Contextual Model and Temporal Gate Pooling for Speaker IdentificationCode0
Integrated Semantic and Phonetic Post-correction for Chinese Speech RecognitionCode0
A Dataset for Speech Emotion Recognition in Greek Theatrical PlaysCode0
Interpersonal Relationship Labels for the CALLHOME CorpusCode0
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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