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 40514100 of 6433 papers

TitleStatusHype
Discriminative Multi-modality Speech RecognitionCode1
Exploring TTS without T Using Biologically/Psychologically Motivated Neural Network Modules (ZeroSpeech 2020)Code0
Quantitative Analysis of Image Classification Techniques for Memory-Constrained Devices0
Listen Attentively, and Spell Once: Whole Sentence Generation via a Non-Autoregressive Architecture for Low-Latency Speech Recognition0
Incremental Learning for End-to-End Automatic Speech Recognition0
CTC-synchronous Training for Monotonic Attention ModelCode1
ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global ContextCode1
RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions0
The Perceptimatic English Benchmark for Speech Perception Models0
Community Detection Clustering via Gumbel Softmax0
End-to-end Whispered Speech Recognition with Frequency-weighted Approaches and Pseudo Whisper Pre-training0
Off-the-shelf deep learning is not enough: parsimony, Bayes and causality0
Does Visual Self-Supervision Improve Learning of Speech Representations for Emotion Recognition?0
Fast and Robust Unsupervised Contextual Biasing for Speech Recognition0
MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech0
A language score based output selection method for multilingual speech recognition0
Using Automatic Speech Recognition in Spoken Corpus Curation0
Corpus Generation for Voice Command in Smart Home and the Effect of Speech Synthesis on End-to-End SLU0
On Construction of the ASR-oriented Indian English Pronunciation Dictionary0
Parallel Corpus for Japanese Spoken-to-Written Style Conversion0
CEASR: A Corpus for Evaluating Automatic Speech Recognition0
Automatic Speech Recognition for Uyghur through Multilingual Acoustic Modeling0
Preparation of Bangla Speech Corpus from Publicly Available Audio \& Text0
RSC: A Romanian Read Speech Corpus for Automatic Speech Recognition0
Evaluating and Improving Child-Directed Automatic Speech Recognition0
Evaluation of Off-the-shelf Speech Recognizers Across Diverse Dialogue Domains0
Large Corpus of Czech Parliament Plenary Hearings0
Artie Bias Corpus: An Open Dataset for Detecting Demographic Bias in Speech Applications0
The SAFE-T Corpus: A New Resource for Simulated Public Safety Communications0
Development and Evaluation of Speech Synthesis Corpora for Latvian0
ATC-ANNO: Semantic Annotation for Air Traffic Control with Assistive Auto-Annotation0
Improving Speech Recognition for the Elderly: A New Corpus of Elderly Japanese Speech and Investigation of Acoustic Modeling for Speech Recognition0
Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications - A Case Study on German Oral History Interviews0
Where are we in Named Entity Recognition from Speech?0
Automatic Transcription Challenges for Inuktitut, a Low-Resource Polysynthetic Language0
Towards Building an Automatic Transcription System for Language Documentation: Experiences from Muyu0
Class-based LSTM Russian Language Model with Linguistic Information0
ArzEn: A Speech Corpus for Code-switched Egyptian Arabic-English0
Analysis of GlobalPhone and Ethiopian Languages Speech Corpora for Multilingual ASR0
Malayalam Speech Corpus: Design and Development for Dravidian Language0
A CLARIN Transcription Portal for Interview Data0
Large Vocabulary Read Speech Corpora for Four Ethiopian Languages: Amharic, Tigrigna, Oromo and Wolaytta0
Samr\'omur: Crowd-sourcing Data Collection for Icelandic Speech Recognition0
CoBiLiRo: A Research Platform for Bimodal Corpora0
Macsen: A Voice Assistant for Speakers of a Lesser Resourced LanguageCode0
DNN-Based Multilingual Automatic Speech Recognition for Wolaytta using Oromo Speech0
Automatically Assess Children's Reading Skills0
Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration0
Improving the Language Model for Low-Resource ASR with Online Text Corpora0
Crossing the SSH Bridge with Interview Data0
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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