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 22012250 of 6433 papers

TitleStatusHype
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge0
A Panoramic Survey of Natural Language Processing in the Arab World0
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices0
Cache-Augmented Latent Topic Language Models for Speech Retrieval0
Bytes are All You Need: End-to-End Multilingual Speech Recognition and Synthesis with Bytes0
A PAC-Bayesian Approach to Minimum Perplexity Language Modeling0
Byte Pair Encoding Is All You Need For Automatic Bengali Speech Recognition0
Byte-based Neural Machine Translation0
``Oh, I've Heard That Before'': Modelling Own-Dialect Bias After Perceptual Learning by Weighting Training Data0
LegoSLM: Connecting LLM with Speech Encoder using CTC Posteriors0
Bypass Temporal Classification: Weakly Supervised Automatic Speech Recognition with Imperfect Transcripts0
序列標記與配對方法用於語音辨識錯誤偵測及修正 (On the Use of Sequence Labeling and Matching Methods for ASR Error Detection and Correction) [In Chinese]0
BUT System for the MLC-SLM Challenge0
BUT Opensat 2019 Speech Recognition System0
Advancing Multi-talker ASR Performance with Large Language Models0
Building Text-To-Speech Voices in the Cloud0
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline0
An Unsupervised Speaker Clustering Technique based on SOM and I-vectors for Speech Recognition Systems0
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis0
Building Open-source Speech Technology for Low-resource Minority Languages with SáMi as an Example – Tools, Methods and Experiments0
An Unsupervised Parameter Estimation Algorithm for a Generative Dependency N-gram Language Model0
Advancing Momentum Pseudo-Labeling with Conformer and Initialization Strategy0
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy0
Evaluating and Improving Automatic Speech Recognition Systems for Korean Meteorological Experts0
Evaluating and Improving Child-Directed Automatic Speech Recognition0
Evaluating Automatic Speech Recognition in Translation0
Evaluating Word Embeddings for Sentence Boundary Detection in Speech Transcripts0
Building Open Javanese and Sundanese Corpora for Multilingual Text-to-Speech0
Building and curating conversational corpora for diversity-aware language science and technology0
An Unsupervised Approach to User Simulation: Toward Self-Improving Dialog Systems0
Building Intelligent Autonomous Navigation Agents0
Building English ASR model with regional language support0
An Ultra-low Power RNN Classifier for Always-On Voice Wake-Up Detection Robust to Real-World Scenarios0
Advancing Hearing Assessment: An ASR-Based Frequency-Specific Speech Test for Diagnosing Presbycusis0
Anti-spoofing Methods for Automatic SpeakerVerification System0
Building competitive direct acoustics-to-word models for English conversational speech recognition0
Advancing CTC-CRF Based End-to-End Speech Recognition with Wordpieces and Conformers0
Building bilingual lexicon to create Dialect Tunisian corpora and adapt language model0
Building a Unified Code-Switching ASR System for South African Languages0
Answer Fast: Accelerating BERT on the Tensor Streaming Processor0
A Conformer-based ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement and Speech Separation0
Étude de l'informativité des transcriptions : une approche basée sur le résumé automatique0
Building a synchronous corpus of acoustic and 3D facial marker data for adaptive audio-visual speech synthesis0
Building a Public Domain Voice Database for Odia0
An Overview on Language Models: Recent Developments and Outlook0
Building a Non-native Speech Corpus Featuring Chinese-English Bilingual Children: Compilation and Rationale0
Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems0
An Overview on Data Representation Learning: From Traditional Feature Learning to Recent Deep Learning0
Advancing Connectionist Temporal Classification With Attention Modeling0
Building and Evaluation of a Real Room Impulse Response Dataset0
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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