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 10511100 of 6433 papers

TitleStatusHype
On the Problem of Text-To-Speech Model Selection for Synthetic Data Generation in Automatic Speech Recognition0
A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method0
Attention based end to end Speech Recognition for Voice Search in Hindi and English0
Alignment Restricted Streaming Recurrent Neural Network Transducer0
Attention-Based End-to-End Speech Recognition on Voice Search0
Alignment Knowledge Distillation for Online Streaming Attention-based Speech Recognition0
A Cycle-GAN Approach to Model Natural Perturbations in Speech for ASR Applications0
Cache-Augmented Latent Topic Language Models for Speech Retrieval0
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge0
Attention-based ASR with Lightweight and Dynamic Convolutions0
Alignment-Free Training for Transducer-based Multi-Talker ASR0
Alignment Entropy Regularization0
Attacks as Defenses: Designing Robust Audio CAPTCHAs Using Attacks on Automatic Speech Recognition Systems0
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition0
Byte-based Neural Machine Translation0
A Treatise On FST Lattice Based MMI Training0
Alignment-Based Neural Machine Translation0
Aligning Speech to Languages to Enhance Code-switching Speech Recognition0
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition0
Activity focused Speech Recognition of Preschool Children in Early Childhood Classrooms0
A collaborative filtering model with heterogeneous neural networks for recommender systems0
Byte Pair Encoding Is All You Need For Automatic Bengali Speech Recognition0
A Tour of TensorFlow0
Aligning Pre-trained Models for Spoken Language Translation0
A Toolkit for Joint Speaker Diarization and Identification with Application to Speaker-Attributed ASR0
Aligner-Encoders: Self-Attention Transformers Can Be Self-Transducers0
A Code-Switching Corpus of Turkish-German Conversations0
Regularization Advantages of Multilingual Neural Language Models for Low Resource Domains0
A Token-Wise Beam Search Algorithm for RNN-T0
A three-dimensional approach to Visual Speech Recognition using Discrete Cosine Transforms0
A Lightweight Speaker Recognition System Using Timbre Properties0
A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems0
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis0
Active Learning for Speech Recognition: the Power of Gradients0
使用字典學習法於強健性語音辨識(The Use of Dictionary Learning Approach for Robustness Speech Recognition) [In Chinese]0
0/1 Deep Neural Networks via Block Coordinate Descent0
Bytes are All You Need: End-to-End Multilingual Speech Recognition and Synthesis with Bytes0
CAFE A Novel Code switching Dataset for Algerian Dialect French and English0
Can Generative Large Language Models Perform ASR Error Correction?0
Can You Repeat That? Using Word Repetition to Improve Spoken Term Detection0
Challenges and Solutions for Consistent Annotation of Vietnamese Treebank0
A Text Normalisation System for Non-Standard English Words0
A Temporal Simulator for Developing Turn-Taking Methods for Spoken Dialogue Systems0
A light-weight and efficient punctuation and word casing prediction model for on-device streaming ASR0
ATCSpeechNet: A multilingual end-to-end speech recognition framework for air traffic control systems0
ATCSpeech: a multilingual pilot-controller speech corpus from real Air Traffic Control environment0
Algorithms For Automatic Accentuation And Transcription Of Russian Texts In Speech Recognition Systems0
A Coarse-Grained Model for Optimal Coupling of ASR and SMT Systems for Speech Translation0
ATC-ANNO: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation0
A Lexical-aware Non-autoregressive Transformer-based ASR Model0
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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