Statistical mapping between articulatory and acoustic data for an ultrasound-based silent speech interface

Hueber, Thomas; Benaroya, Elie-Laurent; Denby, B.; Chollet, Gérard

doi:10.21437/interspeech.2011-239

Cited by 22 publications

(1 citation statement)

References 31 publications

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“…Sinyal wicara adalah bentuk komunikasi yang kompleks dan terdiri dari dua komponen utama: sinyal akustik dan aspek linguistik atau artikulasi [3], [4]. (1) Sinyal Akustik yaitu aspek fisik dari sinyal wicara.…”

Section: Pendahuluanunclassified

Klasifikasi Sinyal Wicara Untuk Gerakan Kursi Roda Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation

Wisaksono,

Hindarto,

Efiyanti

et al. 2024

Transmisi J.Ilm. Tek. Elekt.

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Kursi Roda yang dikendalikan oleh sinyal wicara adalah teknologi bantuan yang inovatif dirancang untuk meningkatkan mobilitas dan kemandirian penyandang disabilitas. Penelitian ini bertujuan untuk mengkalsifikasi sinyal wicara yang digunakan untuk Gerakan kursi roda yang dapat dioperasikan menggunakan perintah suara. Ada lima jenis data perintah wicara yang harus dikenali yaitu maju, mundur, kiri, kanan, dan berhenti. Terdapat beberapa ekstrasi fitur yang digunakan, yaitu menggunakan metode FFT dengan mengambil nilai energi rata-rata, dan menggunakan metode DWT dengan mengambil nilai subband energi dan nilai zero crossing threshold. Proses klasifikasi yang digunakan menggunakan metode Jaringan Syaraf Tiruan Backpropagation. Penelitian yang diujikan menggunakan metode Jringn Syaraf Tiruan menghasilkan tingkat akurasi yang lebih baik dengan menggunakan hidden layer 2 dan hidden layer 3. Hasil akurasi yang didapatkan sebesar 100% untuk proses pelatihan dan 100% untuk proses pengujian

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Section: Pendahuluanunclassified

Klasifikasi Sinyal Wicara Untuk Gerakan Kursi Roda Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation

Wisaksono,

Hindarto,

Efiyanti

et al. 2024

Transmisi J.Ilm. Tek. Elekt.

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Transition Model from Articulatory Domain to Acoustic Domain of Phoneme Using SVM for Regression: Towards a Silent Spoken Communication

Bencheikh¹,

Cherkaoui²

2019

Advances in Intelligent Systems and Computing

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Silent Speech Interfaces for Speech Restoration: A Review

et al. 2020

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This review summarises the status of silent speech interface (SSI) research. SSIs rely on non-acoustic biosignals generated by the human body during speech production to enable communication whenever normal verbal communication is not possible or not desirable. In this review, we focus on the first case and present latest SSI research aimed at providing new alternative and augmentative communication methods for persons with severe speech disorders. SSIs can employ a variety of biosignals to enable silent communication, such as electrophysiological recordings of neural activity, electromyographic (EMG) recordings of vocal tract movements or the direct tracking of articulator movements using imaging techniques. Depending on the disorder, some sensing techniques may be better suited than others to capture speech-related information. For instance, EMG and imaging techniques are well suited for laryngectomised patients, whose vocal tract remains almost intact but are unable to speak after the removal of the vocal folds, but fail for severely paralysed individuals. From the biosignals, SSIs decode the intended message, using automatic speech recognition or speech synthesis algorithms. Despite considerable advances in recent years, most present-day SSIs have only been validated in laboratory settings for healthy users. Thus, as discussed in this paper, a number of challenges remain to be addressed in future research before SSIs can be promoted to real-world applications. If these issues can be addressed successfully, future SSIs will improve the lives of persons with severe speech impairments by restoring their communication capabilities.

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Statistical mapping between articulatory and acoustic data for an ultrasound-based silent speech interface

Cited by 22 publications

References 31 publications

Klasifikasi Sinyal Wicara Untuk Gerakan Kursi Roda Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation

Klasifikasi Sinyal Wicara Untuk Gerakan Kursi Roda Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation

Transition Model from Articulatory Domain to Acoustic Domain of Phoneme Using SVM for Regression: Towards a Silent Spoken Communication

Silent Speech Interfaces for Speech Restoration: A Review

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