LibriSpeech test-clean

The 'LibriSpeech test-clean' dataset contains clean, high-quality speech recordings used to evaluate word error rate (WER) in automatic speech recognition systems.

Papers using LibriSpeech test-clean (12)

CLEAR: Continuous Latent Autoregressive Modeling for High-quality and Low-latency Speech Synthesis2025 · 7 citesImproving Semi-supervised End-to-end Automatic Speech Recognition Using Cyclegan And Inter-domain Losses2022 · 2 citesClariCodec: Optimising Neural Speech Codes for 200bps Communication using Reinforcement Learning2026Enhancing Fully Formatted End-to-End Speech Recognition with Knowledge Distillation via Multi-Codebook Vector Quantization2025HuBERT-VIC: Improving Noise-Robust Automatic Speech Recognition of Speech Foundation Model via Variance-Invariance-Covariance Regularization2025BR-ASR: Efficient and Scalable Bias Retrieval Framework for Contextual Biasing ASR in Speech LLM2025Pseudo-Autoregressive Neural Codec Language Models for Efficient Zero-Shot Text-to-Speech Synthesis2025Macro-block Dropout For Improved Regularization In Training End-to-end Speech Recognition Models2022Improving Semi-supervised End-to-end Automatic Speech Recognition using CycleGAN and Inter-domain Losses2022Macro-block dropout for improved regularization in training end-to-end speech recognition models2022Dynamic Chunk Convolution for Unified Streaming and Non-Streaming Conformer ASR2023CTC-Assisted LLM-Based Contextual ASR2024