Publications by authors named "Jerome Farinas"

Perceptual measures, such as intelligibility and speech disorder severity, are widely used in the clinical assessment of speech disorders in patients treated for oral or oropharyngeal cancer. Despite their widespread usage, these measures are known to be subjective and hard to reproduce. Therefore, an M-Health assessment based on an automatic prediction has been seen as a more robust and reliable alternative.

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Reliable fundamental frequency (f) extraction algorithms are crucial in many fields of speech research. The current bulk of studies testing the robustness of different algorithms have focused on healthy speech and/or measurements of sustained vowels. Few studies have tested f estimations in the context of pathological speech, and even fewer on continuous speech.

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Background: In head and neck cancer, many tools exist to measure speech impairment, but few evaluate the impact on communication abilities. Some self-administered questionnaires are available to assess general activity limitations including communication. Others are not validated in oncology.

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Purpose: The constitution of social circles around patients treated for cancer of the upper aerodigestive tract (UADT) has a major influence on factors that affect quality of life (QOL) but is poorly assessed, mainly due to a lack of tools. The objective of this study is to develop a questionnaire that assesses the constitution of social circles in a population treated for UADT cancer and to analyze the construct (structural and clinical validity) and criterion validity.

Methods: The Evaluation of the Constitution of Social Circles (ECSC) questionnaire was developed in French by a committee of experts.

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Background: Speech disorders impact quality of life for patients treated with oral cavity and oropharynx cancers. However, there is a lack of uniform and applicable methods for measuring the impact on speech production after treatment in this tumor location.

Objective: The objective of this work is to (1) model an automatic severity index of speech applicable in clinical practice, that is equivalent or superior to a severity score obtained by human listeners, via several acoustics parameters extracted (a) directly from speech signal and (b) resulting from speech processing and (2) derive an automatic speech intelligibility classification (i.

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Purpose: To validate the upgraded version of the CHI with two new dimensions ("limitation of neck and/or shoulder movements", "changes in physical appearance"). To assess the relationship between CHI scores and patient self-reported management needs.

Methods: 71 patients treated for cancer with ENT complaints and 36 controls were included.

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Context: Nowadays, clinical tools are available to evaluate the functional impact of speech disorders in neurological conditions, but few are validated in oncology. Because of their location, cancers of the upper aerodigestive tract directly impact patients' communication skills. Two questionnaires exist in French, the Speech Handicap Index (SHI) and the Phonation Handicap Index (PHI), but none are specifically validated for the head and neck cancer population.

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Background: The development of automatic tools based on acoustic analysis allows to overcome the limitations of perceptual assessment for patients with head and neck cancer. The aim of this study is to provide a systematic review of literature describing the effects of oral and oropharyngeal cancer on speech intelligibility using acoustic analysis.

Methods: Two databases (PubMed and Embase) were surveyed.

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Purpose: The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist audiologists/hearing-aid dispensers in the fine-tuning of hearing aids.

Method: Sixty young participants with normal hearing listened to speech materials mimicking the perceptual consequences of ARHL at different levels of severity.

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Bouts of vocalizations given by seven red deer stags were recorded over the rutting period, and homomorphic analysis and hidden Markov models (two techniques typically used for the automatic recognition of human speech utterances) were used to investigate whether the spectral envelope of the calls was individually distinctive. Bouts of common roars (the most common call type) were highly individually distinctive, with an average recognition percentage of 93.5%.

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