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Speech Intelligibility

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A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions.

The Journal of the Acoustical Society of America
Deep learning based speech separation or noise reduction needs to generalize to voices not encountered during training and to operate under multiple corruptions. The current study provides such a demonstration for hearing-impaired (HI) listeners. Sen...

Speech Vision: An End-to-End Deep Learning-Based Dysarthric Automatic Speech Recognition System.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dysarthria is a disorder that affects an individual's speech intelligibility due to the paralysis of muscles and organs involved in the articulation process. As the condition is often associated with physically debilitating disabilities, not only do ...

On training targets for deep learning approaches to clean speech magnitude spectrum estimation.

The Journal of the Acoustical Society of America
Estimation of the clean speech short-time magnitude spectrum (MS) is key for speech enhancement and separation. Moreover, an automatic speech recognition (ASR) system that employs a front-end relies on clean speech MS estimation to remain robust. Tra...

An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners.

The Journal of the Acoustical Society of America
Real-time operation is critical for noise reduction in hearing technology. The essential requirement of real-time operation is causality-that an algorithm does not use future time-frame information and, instead, completes its operation by the end of ...

Deep learning based speaker separation and dereverberation can generalize across different languages to improve intelligibility.

The Journal of the Acoustical Society of America
The practical efficacy of deep learning based speaker separation and/or dereverberation hinges on its ability to generalize to conditions not employed during neural network training. The current study was designed to assess the ability to generalize ...

A causal and talker-independent speaker separation/dereverberation deep learning algorithm: Cost associated with conversion to real-time capable operation.

The Journal of the Acoustical Society of America
The fundamental requirement for real-time operation of a speech-processing algorithm is causality-that it operate without utilizing future time frames. In the present study, the performance of a fully causal deep computational auditory scene analysis...

Regional Language Speech Recognition from Bone-Conducted Speech Signals through Different Deep Learning Architectures.

Computational intelligence and neuroscience
Bone-conducted microphone (BCM) senses vibrations from bones in the skull during speech to electrical audio signal. When transmitting speech signals, bone-conduction microphones (BCMs) capture speech signals based on the vibrations of the speaker's s...

A Deep Learning Based Approach to Synthesize Intelligible Speech with Limited Temporal Envelope Information.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Envelope waveforms can be extracted from multiple frequency bands of a speech signal, and envelope waveforms carry important intelligibility information for human speech communication. This study aimed to investigate whether a deep learning-based mod...

A Novel Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech and enhanced speech signals. Despite improving the speech quality, su...

Restoring speech intelligibility for hearing aid users with deep learning.

Scientific reports
Almost half a billion people world-wide suffer from disabling hearing loss. While hearing aids can partially compensate for this, a large proportion of users struggle to understand speech in situations with background noise. Here, we present a deep l...