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 60016050 of 6433 papers

TitleStatusHype
Situated Incremental Natural Language Understanding using a Multimodal, Linguistically-driven Update Model0
Class-Based Language Modeling for Translating into Morphologically Rich Languages0
Confusion Network for Arabic Name Disambiguation and Transliteration in Statistical Machine Translation0
Quality Estimation for Automatic Speech Recognition0
Recurrent Neural Network-based Tuple Sequence Model for Machine Translation0
A PAC-Bayesian Approach to Minimum Perplexity Language Modeling0
Learning from 26 Languages: Program Management and Science in the Babel Program0
The Effect of Sensor Errors in Situated Human-Computer Dialogue0
Automatically building a Tunisian Lexicon for Deverbal Nouns0
Key Event Detection in Video using ASR and Visual Data0
Employing Phonetic Speech Recognition for Language and Dialect Specific Search0
Developing further speech recognition resources for Welsh0
Trainable and Dynamic Computing: Error Backpropagation through Physical Media0
Recognition of Isolated Words using Zernike and MFCC features for Audio Visual Speech Recognition0
Building DNN Acoustic Models for Large Vocabulary Speech RecognitionCode0
On the Use of Different Feature Extraction Methods for Linear and Non Linear kernels0
Dropout: A Simple Way to Prevent Neural Networks from Overfitting0
Towards End-To-End Speech Recognition with Recurrent Neural Networks0
Markovian Discriminative Modeling for Dialog State Tracking0
Optimizing Generative Dialog State Tracker via Cascading Gradient Descent0
Alex: Bootstrapping a Spoken Dialogue System for a New Domain by Real Users0
SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue0
Evaluating a Spoken Dialogue System that Detects and Adapts to User Affective States0
Aided diagnosis of dementia type through computer-based analysis of spontaneous speech0
InproTKs: A Toolkit for Incremental Situated Processing0
Word-Based Dialog State Tracking with Recurrent Neural Networks0
MVA: The Multimodal Virtual Assistant0
Revisiting Word Neighborhoods for Speech Recognition0
Extrinsic Evaluation of Dialog State Tracking and Predictive Metrics for Dialog Policy Optimization0
Dive deeper: Deep Semantics for Sentiment Analysis0
The SJTU System for Dialog State Tracking Challenge 20
Comparative Error Analysis of Dialog State Tracking0
Free on-line speech recogniser based on Kaldi ASR toolkit producing word posterior lattices0
Unsupervised Adaptation for Statistical Machine Translation0
The PARLANCE mobile application for interactive search in English and Mandarin0
Detecting Health Related Discussions in Everyday Telephone Conversations for Studying Medical Events in the Lives of Older Adults0
Sequential Labeling for Tracking Dynamic Dialog States0
Using Ellipsis Detection and Word Similarity for Transformation of Spoken Language into Grammatically Valid Sentences0
Bayesian Reordering Model with Feature Selection0
A Demonstration of Dialogue Processing in SimSensei Kiosk0
Web-style ranking and SLU combination for dialog state tracking0
Dialogue Strategy Learning in Healthcare: A Systematic Approach for Learning Dialogue Models from Data0
LingSync \& the Online Linguistic Database: New Models for the Collection and Management of Data for Language Communities, Linguists and Language Learners0
Automatic evaluation of spoken summaries: the case of language assessment0
Speech recognition in Alzheimer's disease with personal assistive robots0
Preliminary Test of a Real-Time, Interactive Silent Speech Interface Based on Electromagnetic Articulograph0
Individuality-preserving Voice Conversion for Articulation Disorders Using Dictionary Selective Non-negative Matrix Factorization0
Syllable and language model based features for detecting non-scorable tests in spoken language proficiency assessment applications0
Automated scoring of speaking items in an assessment for teachers of English as a Foreign Language0
Short-Term Projects, Long-Term Benefits: Four Student NLP Projects for Low-Resource Languages0
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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