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 60516100 of 6433 papers

TitleStatusHype
Boosting the Transferability of Audio Adversarial Examples with Acoustic Representation Optimization0
Bootstrap an end-to-end ASR system by multilingual training, transfer learning, text-to-text mapping and synthetic audio0
Bootstrapping Method for Developing Part-of-Speech Tagged Corpus in Low Resource Languages Tagset - A Focus on an African Igbo0
Borrow a Little from your Rich Cousin: Using Embeddings and Polarities of English Words for Multilingual Sentiment Classification0
Bounds on mutual information of mixture data for classification tasks0
Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition0
Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding0
BRDS: An FPGA-based LSTM Accelerator with Row-Balanced Dual-Ratio Sparsification0
Breaking the Data Barrier: Towards Robust Speech Translation via Adversarial Stability Training0
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages0
Breaking Through the Spike: Spike Window Decoding for Accelerated and Precise Automatic Speech Recognition0
Handling Trade-Offs in Speech Separation with Sparsely-Gated Mixture of Experts0
Breaking Walls: Pioneering Automatic Speech Recognition for Central Kurdish: End-to-End Transformer Paradigm0
BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition0
Bridging Speech and Text: Enhancing ASR with Pinyin-to-Character Pre-training in LLMs0
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding0
Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling0
Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks0
Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models0
Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech0
Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition0
Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition0
Broadcast News Story Segmentation Using Manifold Learning on Latent Topic Distributions0
BS-PLCNet: Band-split Packet Loss Concealment Network with Multi-task Learning Framework and Multi-discriminators0
BSTC: A Large-Scale Chinese-English Speech Translation Dataset0
BTS: Back TranScription for Speech-to-Text Post-Processor using Text-to-Speech-to-Text0
BUCEADOR, a multi-language search engine for digital libraries0
Building a 70 billion word corpus of English from ClueWeb0
Building Accurate Low Latency ASR for Streaming Voice Search0
Building a Functional Machine Translation Corpus for Kpelle0
Building a great multi-lingual teacher with sparsely-gated mixture of experts for speech recognition0
Building an ASR Error Robust Spoken Virtual Patient System in a Highly Class-Imbalanced Scenario Without Speech Data0
Building and Evaluation of a Real Room Impulse Response Dataset0
Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems0
Building a Non-native Speech Corpus Featuring Chinese-English Bilingual Children: Compilation and Rationale0
Building a Public Domain Voice Database for Odia0
Building a synchronous corpus of acoustic and 3D facial marker data for adaptive audio-visual speech synthesis0
Building a Unified Code-Switching ASR System for South African Languages0
Building bilingual lexicon to create Dialect Tunisian corpora and adapt language model0
Building competitive direct acoustics-to-word models for English conversational speech recognition0
Building English ASR model with regional language support0
Building Intelligent Autonomous Navigation Agents0
Building and curating conversational corpora for diversity-aware language science and technology0
Building Open Javanese and Sundanese Corpora for Multilingual Text-to-Speech0
Building Open-source Speech Technology for Low-resource Minority Languages with SáMi as an Example – Tools, Methods and Experiments0
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis0
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline0
Building Text-To-Speech Voices in the Cloud0
BUT Opensat 2019 Speech Recognition System0
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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