Ji-Yan Han's research while affiliated with National Chiao Tung University and other places
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Publications (14)
Voice-driven communication assistive systems—speech enhancement (SE), voice conversion (VC), and automatic speech recognition with text-to-speech (ASR-TTS)—are recognized approaches for improving dysarthric speakers’ speech intelligibility. However, which approach performs better for moderate dysarthric patients is unclear. This study compared the...
Objective:
Doctors, nowadays, primarily use auditory-perceptual evaluation, such as the grade, roughness, breathiness, asthenia, and strain scale, to evaluate voice quality and determine the treatment. However, the results predicted by individual physicians often differ, because of subjective perceptions, and diagnosis time interval, if the patien...
Background:
The population of young adults who are hearing impaired increases yearly, and a device that enables convenient hearing screening could help monitor their hearing. However, background noise is a critical issue that limits the capabilities of such a device. Therefore, this study evaluated the effectiveness of commercial active noise canc...
With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three...
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 model with features of temporal envelope information could synthesize an intelligible speech, and to st...
Medical masks have become necessary of late because of the COVID-19 outbreak; however, they tend to attenuate the energy of speech signals and affect speech quality. Therefore, this study proposes an optical-based microphone approach to obtain speech signals from speakers' medical masks. Experimental results showed that the optical-based microphone...
Background and Objective
: Most dysarthric patients encounter communication problems due to unintelligible speech. Currently, there are many voice-driven systems aimed at improving their speech intelligibility; however, the intelligibility performance of these systems are affected by challenging application conditions (e.g., time variance of patien...
Background
Cochlear implant technology is a well-known approach to help deaf individuals hear speech again and can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction, such as noise classification and deep denoi...
Voice control is an important way of controlling mobile devices; however, using it remains a challenge for dysarthric patients. Currently, there are many approaches, such as automatic speech recognition (ASR) systems, being used to help dysarthric patients control mobile devices. However, the large computation power requirement for the ASR system i...
BACKGROUND
The cochlear implant technology is a well-known approach to help deaf patients hear speech again. It can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction (NR), such as noise classification and deep...
Dysarthria is a communication disorder common in people with damaged neuro-muscular apparatus resulting from events such as stroke. For a dysarthric speaker, voice conversion (VC) is one of the well-known approaches to improve speech intelligibility for a dysarthric speaker. Most of the well-known VC methods focus on converting amplitude features w...
BACKGROUND
Voice disorders mainly result from chronic overuse or abuse, particularly for teachers or other occupational voice users. Previous studies have proposed a contact microphone attached to the anterior neck for ambulatory voice monitoring; however, the inconvenience associated with this device and its lack of real-time processing limit its...
Background
Voice disorders mainly result from chronic overuse or abuse, particularly in occupational voice users such as teachers. Previous studies proposed a contact microphone attached to the anterior neck for ambulatory voice monitoring; however, the inconvenience associated with taping and wiring, along with the lack of real-time processing, ha...
Citations
... Regarding speech disorders, the amount of related work is even larger, the Parkinson's disease being one of the main focuses [10,11]. As recent studies, we can also cite [12,13] for the assessment of speech intelligibility for patients suffering from HNC. Considering populations of dysarthric patients, [14,15] propose deep learning-based approaches for the enhancement of speech intelligibility while [16,17] for the assessment of speech disorder severity. Despite the wide range of work, it is very rare to see studies involving patient populations with various causes of speech disorders. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/352635925352450-1461086364456_Q64/Ying-Hui-Lai.jpg)
... Current state-of-the-art ASR systems are typically end-to-end based on autoregressive models [22] or deep learning models [23]. Voice command recognition can be used for controlling robots in simple robotic tasks using hidden Markov models (HMMs) [24] or deep learning [25]. For example, the answer-set rules were designed, and the commands were converted into a sequence of actions for robot task planning [26]. ...
