Pathological speech such as Oesophageal Speech (OS) is difficult to understand due to the
presence of undesired artefacts and lack of normal healthy speech characteristics. Modern …

Simple Summary This paper introduces a new method for cleaning impaired speech by
combining Pareto-optimized deep learning with Non-negative Matrix Factorization (NMF) …

Loss of the larynx significantly alters natural voice production, requiring alternative
communication modalities and rehabilitation methods to restore speech intelligibility and …

This work adapts two recent architectures of generative models and evaluates their
effectiveness for the conversion of whispered speech to normal speech. We incorporate the …

Silent speech interfaces (SSIs) are devices that convert nonaudio bio-signals to speech,
which hold the potential of recovering quality speech for laryngectomees (people who have …

Patients who have had their entire larynx removed, including the vocal folds, owing to throat
cancer may experience difficulties in speaking. In such cases, electrolarynx devices are …

This paper presents application of a speech quality measurement method to evaluate the
naturalness of synthesized speech from Text-To-Speech synthesis (TTS) which is an …

Esophageal speech (ES) is a pathological voice that is often difficult to understand.
Moreover, acquiring recordings of a patient's voice before a laryngectomy proves …

The deep learning-based electrolaryngeal (EL) voice conversion methods have achieved
good results in non-tonal languages. However, the effectiveness in tonal languages, such as …

Voice conversion (VC) is an effective approach to electrolaryngeal (EL) speech
enhancement, a task that aims to improve the quality of the artificial voice from an …