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 651700 of 6433 papers

TitleStatusHype
Language Technology Programme for Icelandic 2019-2023Code0
Language Complexity and Speech Recognition Accuracy: Orthographic Complexity Hurts, Phonological Complexity Doesn'tCode0
Language Identification Using Deep Convolutional Recurrent Neural NetworksCode0
Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech RecognitionCode0
Language-Agnostic Syllabification with Neural Sequence LabelingCode0
An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer LearningCode0
The NPU-ASLP System Description for Visual Speech Recognition in CNVSRC 2024Code0
Language Bootstrapping: Learning Word Meanings From Perception-Action AssociationCode0
lex4all: A language-independent tool for building and evaluating pronunciation lexicons for small-vocabulary speech recognitionCode0
Killkan: The Automatic Speech Recognition Dataset for Kichwa with Morphosyntactic InformationCode0
Key Frame Mechanism For Efficient Conformer Based End-to-end Speech RecognitionCode0
Adaptive Natural Language Generation for Task-oriented Dialogue via Reinforcement LearningCode0
Keyphrase Cloud Generation of Broadcast NewsCode0
KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube VideosCode0
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
Joint CTC-Attention based End-to-End Speech Recognition using Multi-task LearningCode0
Analyzing the impact of speaker localization errors on speech separation for automatic speech recognitionCode0
Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack DetectionCode0
Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptationCode0
Kurdish (Sorani) Speech to Text: Presenting an Experimental DatasetCode0
Intrinsic evaluation of language models for code-switchingCode0
Interpersonal Relationship Labels for the CALLHOME CorpusCode0
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech RecognitionCode0
Analyzing Robustness of End-to-End Neural Models for Automatic Speech RecognitionCode0
Analyzing Phonetic and Graphemic Representations in End-to-End Automatic Speech RecognitionCode0
Adaptive Computation Modules: Granular Conditional Computation For Efficient InferenceCode0
Investigating the Effects of Word Substitution Errors on Sentence EmbeddingsCode0
Adaptive Cascading Network for Continual Test-Time AdaptationCode0
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition SystemsCode0
Integrating Emotion Recognition with Speech Recognition and Speaker Diarisation for ConversationsCode0
Integrated Semantic and Phonetic Post-correction for Chinese Speech RecognitionCode0
A Comparison of Adaptation Techniques and Recurrent Neural Network ArchitecturesCode0
Investigating the Emergent Audio Classification Ability of ASR Foundation ModelsCode0
Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wildCode0
Independent and automatic evaluation of acoustic-to-articulatory inversion modelsCode0
Incremental Training of a Recurrent Neural Network Exploiting a Multi-Scale Dynamic MemoryCode0
Improving Unsupervised Sparsespeech Acoustic Models with Categorical ReparameterizationCode0
Improving Voice Separation by Incorporating End-to-end Speech RecognitionCode0
Improving the Inclusivity of Dutch Speech Recognition by Fine-tuning Whisper on the JASMIN-CGN CorpusCode0
A Comparative Study on Transformer vs RNN in Speech ApplicationsCode0
Instant One-Shot Word-Learning for Context-Specific Neural Sequence-to-Sequence Speech RecognitionCode0
Analysis of French Phonetic Idiosyncrasies for Accent RecognitionCode0
Analysis of EEG frequency bands for Envisioned Speech RecognitionCode0
Adapting the adapters for code-switching in multilingual ASRCode0
Improving LSTM-CTC based ASR performance in domains with limited training dataCode0
Improving Children's Speech Recognition by Fine-tuning Self-supervised Adult Speech RepresentationsCode0
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model DecodingCode0
Improving CTC-based speech recognition via knowledge transferring from pre-trained language modelsCode0
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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