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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 1001–1050 of 3012 papers

TitleStatusHype
DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distributionCode0
2-bit Conformer quantization for automatic speech recognition—0
Improving Scheduled Sampling for Neural Transducer-based ASR—0
Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator—0
INTapt: Information-Theoretic Adversarial Prompt Tuning for Enhanced Non-Native Speech Recognition—0
Svarah: Evaluating English ASR Systems on Indian Accents—0
ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition—0
Iteratively Improving Speech Recognition and Voice Conversion—0
InterFormer: Interactive Local and Global Features Fusion for Automatic Speech Recognition—0
Incorporating Ultrasound Tongue Images for Audio-Visual Speech Enhancement through Knowledge Distillation—0
BA-SOT: Boundary-Aware Serialized Output Training for Multi-Talker ASR—0
TranUSR: Phoneme-to-word Transcoder Based Unified Speech Representation Learning for Cross-lingual Speech Recognition—0
Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding—0
Personalized Predictive ASR for Latency Reduction in Voice Assistants—0
On the Transferability of Whisper-based Representations for "In-the-Wild" Cross-Task Downstream Speech Applications—0
SE-Bridge: Speech Enhancement with Consistent Brownian Bridge—0
Evaluating OpenAI's Whisper ASR for Punctuation Prediction and Topic Modeling of life histories of the Museum of the Person—0
Text Generation with Speech Synthesis for ASR Data Augmentation—0
GNCformer Enhanced Self-attention for Automatic Speech Recognition—0
On the Efficacy and Noise-Robustness of Jointly Learned Speech Emotion and Automatic Speech Recognition—0
Semantic VAD: Low-Latency Voice Activity Detection for Speech Interaction—0
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages—0
Self-supervised representations in speech-based depression detection—0
BAT: Boundary aware transducer for memory-efficient and low-latency ASR—0
Unsupervised ASR via Cross-Lingual Pseudo-Labeling—0
A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks—0
A Lexical-aware Non-autoregressive Transformer-based ASR Model—0
Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation Based Voice Conversion—0
Critical Appraisal of Artificial Intelligence-Mediated Communication—0
OOD-Speech: A Large Bengali Speech Recognition Dataset for Out-of-Distribution Benchmarking—0
Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations—0
Investigating the Sensitivity of Automatic Speech Recognition Systems to Phonetic Variation in L2 Englishes—0
Masked Audio Text Encoders are Effective Multi-Modal Rescorers—0
Quran Recitation Recognition using End-to-End Deep Learning—0
Exploration of Language Dependency for Japanese Self-Supervised Speech Representation Models—0
Who Needs Decoders? Efficient Estimation of Sequence-level Attributes—0
Multi-Temporal Lip-Audio Memory for Visual Speech Recognition—0
Lookahead When It Matters: Adaptive Non-causal Transformers for Streaming Neural Transducers—0
Employing Hybrid Deep Neural Networks on Dari Speech—0
End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders—0
Hybrid Transducer and Attention based Encoder-Decoder Modeling for Speech-to-Text Tasks—0
A Study on the Integration of Pipeline and E2E SLU systems for Spoken Semantic Parsing toward STOP Quality Challenge—0
Building a Non-native Speech Corpus Featuring Chinese-English Bilingual Children: Compilation and Rationale—0
Towards Better Domain Adaptation for Self-supervised Models: A Case Study of Child ASRCode0
Deep Transfer Learning for Automatic Speech Recognition: Towards Better Generalization—0
Understanding Shared Speech-Text Representations—0
Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition—0
Non-autoregressive End-to-end Approaches for Joint Automatic Speech Recognition and Spoken Language Understanding—0
OLISIA: a Cascade System for Spoken Dialogue State TrackingCode0
Towards the Universal Defense for Query-Based Audio Adversarial Attacks—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