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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

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Showing 2001–2050 of 3012 papers

TitleStatusHype
Lightly Supervised Quality Estimation—0
Lightweight and Robust Multi-Channel End-to-End Speech Recognition with Spherical Harmonic Transform—0
Lightweight End-to-End Speech Recognition from Raw Audio Data Using Sinc-Convolutions—0
Lightweight Prompt Biasing for Contextualized End-to-End ASR Systems—0
Lightweight Target-Speaker-Based Overlap Transcription for Practical Streaming ASR—0
Linguistic-Enhanced Transformer with CTC Embedding for Speech Recognition—0
LinTO Audio and Textual Datasets to Train and Evaluate Automatic Speech Recognition in Tunisian Arabic Dialect—0
LinTO Platform: A Smart Open Voice Assistant for Business Environments—0
LipDiffuser: Lip-to-Speech Generation with Conditional Diffusion Models—0
Listen Again and Choose the Right Answer: A New Paradigm for Automatic Speech Recognition with Large Language Models—0
Listening Comprehension over Argumentative Content—0
Listening while Speaking: Speech Chain by Deep Learning—0
Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End—0
LiSTra, Automatic Speech Translation: English to Lingala case study—0
LiSTra Automatic Speech Translation: English to Lingala Case Study—0
LiteVSR: Efficient Visual Speech Recognition by Learning from Speech Representations of Unlabeled Data—0
LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale—0
LLM-based phoneme-to-grapheme for phoneme-based speech recognition—0
LM-SPT: LM-Aligned Semantic Distillation for Speech Tokenization—0
Local Feature or Mel Frequency Cepstral Coefficients - Which One is Better for MLN-Based Bangla Speech Recognition?—0
Locality enhanced dynamic biasing and sampling strategies for contextual ASR—0
Local Monotonic Attention Mechanism for End-to-End Speech and Language Processing—0
Lombard Effect for Bilingual Speakers in Cantonese and English: importance of spectro-temporal features—0
LongFNT: Long-form Speech Recognition with Factorized Neural Transducer—0
Incorporating VAD into ASR System by Multi-task Learning—0
Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers—0
Looking Enhances Listening: Recovering Missing Speech Using Images—0
Loquacious Set: 25,000 Hours of Transcribed and Diverse English Speech Recognition Data for Research and Commercial Use—0
LoRA-Whisper: Parameter-Efficient and Extensible Multilingual ASR—0
Loss Landscape Dependent Self-Adjusting Learning Rates in Decentralized Stochastic Gradient Descent—0
Loss Prediction: End-to-End Active Learning Approach For Speech Recognition—0
Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models—0
Lost in Transcription: Identifying and Quantifying the Accuracy Biases of Automatic Speech Recognition Systems Against Disfluent Speech—0
Low Latency ASR for Simultaneous Speech Translation—0
Low-rank Gradient Approximation For Memory-Efficient On-device Training of Deep Neural Network—0
Low-Resource Domain Adaptation for Speech LLMs via Text-Only Fine-Tuning—0
Low-Resourced Speech Recognition for Iu Mien Language via Weakly-Supervised Phoneme-based Multilingual Pre-training—0
Low Resource German ASR with Untranscribed Data Spoken by Non-native Children -- INTERSPEECH 2021 Shared Task SPAPL System—0
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages—0
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition—0
SHARP: An Adaptable, Energy-Efficient Accelerator for Recurrent Neural Network—0
LUPET: Incorporating Hierarchical Information Path into Multilingual ASR—0
LV-CTC: Non-autoregressive ASR with CTC and latent variable models—0
Lyrics-to-Audio Alignment by Unsupervised Discovery of Repetitive Patterns in Vowel Acoustics—0
Machine Speech Chain with One-shot Speaker Adaptation—0
MADI: Inter-domain Matching and Intra-domain Discrimination for Cross-domain Speech Recognition—0
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0—0
Mai Ho'omāuna i ka 'Ai: Language Models Improve Automatic Speech Recognition in Hawaiian—0
Make More of Your Data: Minimal Effort Data Augmentation for Automatic Speech Recognition and Translation—0
Malayalam Speech Corpus: Design and Development for Dravidian Language—0
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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