Jun 17, 2024 · In this work, we present a neural attention network that directly combines multi-channel audio to generate phonetic states without requiring any ...

Integration of multiple microphone data is one of the key ways to achieve robust speech recognition in noisy environments or.

In this work, we present a neural attention network that directly combines multi- channel audio to generate phonetic states without requiring any prior ...

This work presents a neural attention network that directly combines multi-channel audio to generate phonetic states without requiring any prior knowledge ...

Jan 7, 2016 · In this work, we propose a novel attention-based model that enables to learn misaligned and non- stationary multiple input sources for distant ...

In this work, we present a neural attention network that directly combines multi-channel audio to generate phonetic states without requiring any prior knowledge ...

End-to-End Speech Recognition with Auditory Attention for Multi-Microphone Distance Speech Recognition. Conference Paper. Aug 2017. Suyoun Kim ...

Integration of multiple microphone data is one of the key ways to achieve robust speech recognition in noisy environments or when the speaker is located at ...

Auditory Attention is proposed to integrate input from multiple microphones directly within an End-to-End speech recognition model, leveraging the attention ...

Kim and I. Lane, “Recurrent models for auditory attention in multi-microphone distance speech recognition,” arXiv preprint. arXiv:1511.06407, 2015.