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Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

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Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

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On matching data and model in LF-MMI-based dysarthric speech recognition

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In light of steady progress in machine learning, automatic speech recognition (ASR) is entering more and more areas of our daily life, but people with dysarthria and other speech pathologies are left behind. Their voices are underrepresented in the trainin ...

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Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

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On Breathing Pattern Information in Synthetic Speech

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The respiratory system is an integral part of human speech production. As a consequence, there is a close relation between respiration and speech signal, and the produced speech signal carries breathing pattern related information. Speech can also be gener ...

ISCA-INT SPEECH COMMUNICATION ASSOC2022

Novel Methods for Incorporating Prior Knowledge for Automatic Speech Assessment

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Speech signal conveys several kinds of information such as a message, speaker identity, emotional state of the speaker and social state of the speaker. Automatic speech assessment is a broad area that refers to using automatic methods to predict human judg ...

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Utterance Verification-Based Dysarthric Speech Intelligibility Assessment Using Phonetic Posterior Features

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In the literature, the task of dysarthric speech intelligibility assessment has been approached through development of different low-level feature representations, subspace modeling, phone confidence estimation or measurement of automatic speech recognitio ...

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Matching of a test signal to a reference word hypothesis forms the core of many speech processing problems, including objective speech intelligibility assessment. This paper first shows that the comparison of two speech signals can be formulated as matchin ...

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Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings

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Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a system ...

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Automatic Dysarthric Speech Detection Exploiting Pairwise Distance-Based Convolutional Neural Networks

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Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

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Automatic Pathological Speech Intelligibility Assessment Exploiting Subspace-Based Analyses

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Competitive state-of-the-art automatic pathological speech intelligibility measures typically rely on regression training on a large number of features, require a large amount of healthy speech training data, or are applicable only to phonetically balanced ...

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