SOTAVerified

Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1351–1400 of 3012 papers

TitleStatusHype
Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation—0
Homophone-based Label Smoothing in End-to-End Automatic Speech Recognition—0
Houston we have a Divergence: A Subgroup Performance Analysis of ASR Models—0
Enhancing Speech Large Language Models with Prompt-Aware Mixture of Audio Encoders—0
Blending LSTMs into CNNs—0
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR—0
How does end-to-end speech recognition training impact speech enhancement artifacts?—0
An Investigation of Monotonic Transducers for Large-Scale Automatic Speech Recognition—0
How Might We Create Better Benchmarks for Speech Recognition?—0
Comparative Analysis of the wav2vec 2.0 Feature Extractor—0
How to Learn a New Language? An Efficient Solution for Self-Supervised Learning Models Unseen Languages Adaption in Low-Resource Scenario—0
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets—0
How to Train Dependency Parsers with Inexact Search for Joint Sentence Boundary Detection and Parsing of Entire Documents—0
How transferable are features in convolutional neural network acoustic models across languages?—0
Comparing Discrete and Continuous Space LLMs for Speech Recognition—0
HTEC: Human Transcription Error Correction—0
Blending LLMs into Cascaded Speech Translation: KIT's Offline Speech Translation System for IWSLT 2024—0
Experiments on Turkish ASR with Self-Supervised Speech Representation Learning—0
Human and Automatic Speech Recognition Performance on German Oral History Interviews—0
Human-Informed Speakers and Interpreters Analysis in the WAW Corpus and an Automatic Method for Calculating Interpreters' D\'ecalage—0
Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement—0
Comparing Two Basic Methods for Discriminating Between Similar Languages and Varieties—0
Huqariq: A Multilingual Speech Corpus of Native Languages of Peru for Speech Recognition—0
Huqariq: A Multilingual Speech Corpus of Native Languages of Peru forSpeech Recognition—0
Comparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary—0
Hybrid Autoregressive Transducer (hat)—0
Hybrid CTC-Attention based End-to-End Speech Recognition using Subword Units—0
Comparison of Lattice-Free and Lattice-Based Sequence Discriminative Training Criteria for LVCSR—0
Hybridized Feature Extraction and Acoustic Modelling Approach for Dysarthric Speech Recognition—0
Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch—0
H_eval: A new hybrid evaluation metric for automatic speech recognition tasks—0
Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks—0
An investigation of modularity for noise robustness in conformer-based ASR—0
Enhancing Multilingual ASR for Unseen Languages via Language Embedding Modeling—0
Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings—0
Advanced Long-context End-to-end Speech Recognition Using Context-expanded Transformers—0
ICMC-ASR: The ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition Challenge—0
Ideal-LLM: Integrating Dual Encoders and Language-Adapted LLM for Multilingual Speech-to-Text—0
Identifying dialects with textual and acoustic cues—0
Identifying Introductions in Podcast Episodes from Automatically Generated Transcripts—0
Identifying Teacher Questions Using Automatic Speech Recognition in Classrooms—0
IE-CPS Lexicon: An Automatic Speech Recognition Oriented Indian-English Pronunciation Dictionary—0
ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale—0
Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than Others—0
Impact of ASR on Alzheimer’s Disease Detection: All Errors are Equal, but Deletions are More Equal than Others—0
Impact of Dataset on Acoustic Models for Automatic Speech Recognition—0
Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport—0
ASR in German: A Detailed Error Analysis—0
Importance of Different Temporal Modulations of Speech: A Tale of Two Perspectives—0
Self-Supervised Learning for Multi-Channel Neural Transducer—0
Show:102550
← PrevPage 28 of 61Next →
All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1—Unverified
2TM-seq2seqTest WER9.7—Unverified
3CTC/attentionTest WER8.2—Unverified
4LF-MMI TDNNTest WER6.7—Unverified
5Whisper-LLaMATest WER6.6—Unverified
6End2end ConformerTest WER3.9—Unverified
7End2end ConformerTest WER3.7—Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7—Unverified
9CTC/AttentionTest WER1.5—Unverified
10WhisperTest WER1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5—Unverified
2CleanMel-L-maskCER14.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32—Unverified
2Whisper-largev3-finetunedTest WER10.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89—Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98—Unverified