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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 2076–2100 of 3012 papers

TitleStatusHype
Streaming Models for Joint Speech Recognition and Translation—0
Streaming Noise Context Aware Enhancement For Automatic Speech Recognition in Multi-Talker Environments—0
Streaming Punctuation: A Novel Punctuation Technique Leveraging Bidirectional Context for Continuous Speech Recognition—0
Streaming Punctuation for Long-form Dictation with Transformers—0
Streaming Simultaneous Speech Translation with Augmented Memory Transformer—0
Streaming Speech-to-Confusion Network Speech Recognition—0
Streaming Transformer ASR with Blockwise Synchronous Inference—0
Streaming Transformer for Hardware Efficient Voice Trigger Detection and False Trigger Mitigation—0
Streaming Voice Conversion Via Intermediate Bottleneck Features And Non-streaming Teacher Guidance—0
Streaming Voice Query Recognition using Causal Convolutional Recurrent Neural Networks—0
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion—0
Structural Analysis of Hindi Phonetics and A Method for Extraction of Phonetically Rich Sentences from a Very Large Hindi Text Corpus—0
Structured Dialogue Policy with Graph Neural Networks—0
Structured State Space Decoder for Speech Recognition and Synthesis—0
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions—0
Student achievement and French sentence repetition test scores—0
Studying the Similarity of COVID-19 Sounds based on Correlation Analysis of MFCC—0
Study of Indian English Pronunciation Variabilities relative to Received Pronunciation—0
StutterNet: Stuttering Detection Using Time Delay Neural Network—0
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech—0
Style-Talker: Finetuning Audio Language Model and Style-Based Text-to-Speech Model for Fast Spoken Dialogue Generation—0
Sub-8-bit quantization for on-device speech recognition: a regularization-free approach—0
Subword Dictionary Learning and Segmentation Techniques for Automatic Speech Recognition in Tamil and Kannada—0
Sub-word Level Lip Reading With Visual Attention—0
Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition—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