A speech-controlled environmental control system for people with severe dysarthria

Hawley, Mark; Enderby, Pam; Green, Phil; Cunningham, Stuart; Brownsell, Simon; Carmichael, James; Parker, Marcie; Hatzis, Athanassios; O'Neill, Peter; Palmer, Rebecca

doi:10.1016/j.medengphy.2006.06.009

Cited by 78 publications

(60 citation statements)

References 13 publications

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“…Moreover, speech as an interface can provide users with a more real-time communication experience to convey messages, in comparison to traditional hardwired switch based interfaces. Earlier studies have shown that systems that deploy automatic speech recognition (ASR) as an interface in a dysarthric setup can have a lower accuracy than hardwired switch-based systems, but, the final message transfer is around 2.5 times faster than the later, even with mis-recognitions followed by corrections [6,7].…”

Section: Speech Interface and Dysarthriamentioning

confidence: 99%

Model adaptation and adaptive training for the recognition of dysarthric speech

Sehgal¹,

Cunningham²

2015

Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies

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Dysarthria is a neurological speech disorder, which exhibits multi-fold disturbances in the speech production system of an individual and can have a detrimental effect on the speech output. In addition to the data sparseness problems, dysarthric speech is characterised by inconsistencies in the acoustic space making it extremely challenging to model. This paper investigates a variety of baseline speaker independent (SI) systems and its suitability for adaptation. The study also explores the usefulness of speaker adaptive training (SAT) for implicitly annihilating inter-speaker variations in a dysarthric corpus. The paper implements a hybrid MLLR-MAP based approach to adapt the SI and SAT systems. ALL the results reported uses UA-SPEECH dysarthric data. Our best adapted systems gave a significant absolute gain of 11.05% (20.42% relative) over the last published best result in the literature. A statistical analysis performed across various systems and its specific implementation in modelling different dysarthric severity sub-groups, showed that, SAT-adapted systems were more applicable to handle disfluencies of more severe speech and SI systems prepared from typical speech were more apt for modelling speech with low level of severity.

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Section: Speech Interface and Dysarthriamentioning

confidence: 99%

Model adaptation and adaptive training for the recognition of dysarthric speech

Sehgal¹,

Cunningham²

2015

Proceedings of SLPAT 2015: 6th Workshop on Speech and Language Processing for Assistive Technologies

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“…Table 6. Accuracy of the Speech Interface and comparison with other systems: human and commercial ASR on normal speech [36]; commercial and developed systems on dysarthric speech with intelligibility levels: high [9], moderate [11], and low [16].…”

Section: Experiments With Dysarthric Peoplementioning

confidence: 99%

Speech-Based Human and Service Robot Interaction: An Application for Mexican Dysarthric People

Morales

Enríquez

Trujillo-Romero

2013

International Journal of Advanced Robotic Systems

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Dysarthria is a motor speech disorder due to weakness or poor coordination of the speech muscles. This condition can be caused by a stroke, traumatic brain injury, or by a degenerative neurological disease. Commonly, people with this disorder also have muscular dystrophy, which restricts their use of switches or keyboards for communication or control of assistive devices (i.e., an electric wheelchair or a service robot). In this case, speech recognition is an attractive alternative for interaction and control of service robots, despite the difficulty of achieving robust recognition performance. In this paper we present a speech recognition system for human and service robot interaction for Mexican Spanish dysarthric speakers. The core of the system consisted of a Speaker Adaptive (SA) recognition system trained with normal-speech. Features such as on-line control of the language model perplexity and the adding of vocabulary, contribute to high recognition performance. Others, such as assessment and text-to-speech (TTS) synthesis, contribute to a more complete interaction with a service robot. Live tests were performed with two mild dysarthric speakers, achieving recognition accuracies of 90-95% for spontaneous speech and 95-100% of accomplished simulated service robot tasks.

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“…Speech technology can also be used for authentication purposes using cryptology that we can obtain a robust system. Speech recognition eases normal life for physically disabled people [7]. In various studies, computer and electric devices have been controlled by voice.…”

Section: Literature Reviewmentioning

confidence: 99%

A Voice Controlled Web based FTP Tool

MarufÖztürk¹,

Çavuolu²,

Zengi̇n³

2013

IJCA

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File Transfer Protocol (FTP) is a protocol which used for file transfer operation via port 21. Various tools are being used for file transfer management. These tools may be either client or web based. In this work a web based voice controlled ftp tool (Wb-FTP) is proposed. And have measured performance analysis of this tool and compared with other ftp tools. This tool has been designed with Asp.NET and C# language. The developed software is robust enough to cope with all file transfer operations. This study shows that voice control is reliable and preferable for essential ftp operations.

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A speech-controlled environmental control system for people with severe dysarthria

Cited by 78 publications

References 13 publications

Model adaptation and adaptive training for the recognition of dysarthric speech

Model adaptation and adaptive training for the recognition of dysarthric speech

Speech-Based Human and Service Robot Interaction: An Application for Mexican Dysarthric People

A Voice Controlled Web based FTP Tool

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