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Found 9 papers, 3 papers with code
RIR-SF: Room Impulse Response Based Spatial Feature for Multi-channel Multi-talker ASR
Multi-channel multi-talker automatic speech recognition (ASR) presents ongoing challenges within the speech community, particularly when confronted with significant reverberation effects.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
UniX-Encoder: A Universal $X$-Channel Speech Encoder for Ad-Hoc Microphone Array Speech Processing
2) Multi-Task Capability: Beyond the single-task focus of previous systems, UniX-Encoder acts as a robust upstream model, adeptly extracting features for diverse tasks including ASR and speaker recognition.
Challenges and Insights: Exploring 3D Spatial Features and Complex Networks on the MISP Dataset
Multi-channel multi-talker speech recognition presents formidable challenges in the realm of speech processing, marked by issues such as background noise, reverberation, and overlapping speech.
Defense against Adversarial Attacks on Hybrid Speech Recognition using Joint Adversarial Fine-tuning with Denoiser
We propose three defenses--denoiser pre-processor, adversarially fine-tuning ASR model, and adversarially fine-tuning joint model of ASR and denoiser.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multi-Channel Multi-Speaker ASR Using 3D Spatial Feature
Experimental results show that 1) the proposed ALL-In-One model achieved a comparable error rate to the pipelined system while reducing the inference time by half; 2) the proposed 3D spatial feature significantly outperformed (31\% CERR) all previous works of using the 1D directional information in both paradigms.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Adversarial Attacks and Defenses for Speech Recognition Systems
We investigate two threat models: a denial-of-service scenario where fast gradient-sign method (FGSM) or weak projected gradient descent (PGD) attacks are used to degrade the model's word error rate (WER); and a targeted scenario where a more potent imperceptible attack forces the system to recognize a specific phrase.
PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR
We present PyChain, a fully parallelized PyTorch implementation of end-to-end lattice-free maximum mutual information (LF-MMI) training for the so-called \emph{chain models} in the Kaldi automatic speech recognition (ASR) toolkit.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Speaker Diarization with Region Proposal Network
Speaker diarization is an important pre-processing step for many speech applications, and it aims to solve the "who spoke when" problem.
Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
We present Espresso, an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neural machine translation toolkit fairseq.
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Speech Recognition
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Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
