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 110 of 6433 papers

TitleStatusHype
NonverbalTTS: A Public English Corpus of Text-Aligned Nonverbal Vocalizations with Emotion Annotations for Text-to-Speech0
Task-Specific Audio Coding for Machines: Machine-Learned Latent Features Are Codes for That Machine0
WhisperKit: On-device Real-time ASR with Billion-Scale Transformers0
VisualSpeaker: Visually-Guided 3D Avatar Lip Synthesis0
A Hybrid Machine Learning Framework for Optimizing Crop Selection via Agronomic and Economic Forecasting0
First Steps Towards Voice Anonymization for Code-Switching SpeechCode0
MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech EnhancementCode2
VOICE CONTROL ROBOT USING ARDUINO MANAGEMENT SYSTEM PROJECT.0
Lightweight Target-Speaker-Based Overlap Transcription for Practical Streaming ASR0
Multimodal Representation Learning and Fusion0
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Benchmark Results

#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
10SE-WSBO With LMWord Error Rate (WER)4.1Unverified