相关论文: Pathological Voice Classification Using Mel-Cepstr…
Depression is the most common psychological disorder and is considered as a leading cause of disability and suicide worldwide. An automated system capable of detecting signs of depression in human speech can contribute to ensuring timely…
In this paper, we try to investigate the presence of cues about the COVID-19 disease in the speech data. We use an approach that is similar to speaker recognition. Each sentence is represented as super vectors of short term Mel filter bank…
Stuttering is a varied speech disorder that harms an individual's communication ability. Persons who stutter (PWS) often use speech therapy to cope with their condition. Improving speech recognition systems for people with such non-typical…
Challenges based on Computational Paralinguistics in the INTERSPEECH Conference have always had a good reception among the attendees owing to its competitive academic and research demands. This year, the INTERSPEECH 2020 Computational…
Depression is a common mental disorder worldwide which causes a range of serious outcomes. The diagnosis of depression relies on patient-reported scales and psychiatrist interview which may lead to subjective bias. In recent years, more and…
This paper addresses the issue of cough detection using only audio recordings, with the ultimate goal of quantifying and qualifying the degree of pathology for patients suffering from respiratory diseases, notably mucoviscidosis. A large…
With the development of computer -systems that can collect and analyze enormous volumes of data, the medical profession is establishing several non-invasive tools. This work attempts to develop a non-invasive technique for identifying…
Head and Neck Cancers (HNC) significantly impact patients' ability to speak, affecting their quality of life. Commonly used metrics for assessing pathological speech are subjective, prompting the need for automated and unbiased evaluation…
Objective: Voice disorders significantly compromise individuals' ability to speak in their daily lives. Without early diagnosis and treatment, these disorders may deteriorate drastically. Thus, automatic classification systems at home are…
A wide range of respiratory diseases, such as cold and flu, asthma, and COVID-19, affect people's daily lives worldwide. In medical practice, respiratory sounds are widely used in medical services to diagnose various respiratory illnesses…
Vocal fatigue refers to the feeling of tiredness and weakness of voice due to extended utilization. This paper investigates the effectiveness of neural embeddings for the detection of vocal fatigue. We compare x-vectors, ECAPA-TDNN, and…
On average the lack of biological markers causes a one year diagnostic delay to detect amyotrophic lateral sclerosis (ALS). To improve the diagnostic process an automatic voice assessment based on acoustic analysis can be used. The purpose…
Around 466 million people worldwide (over 5% of the world's population) have disabling hearing loss, and out of these 34 million are children. Estimates suggest that by 2050, over 900 million people worldwide will have disabling hearing…
This work explores the effect of gender and linguistic-based vocal variations on the accuracy of emotive expression classification. Emotive expressions are considered from the perspective of spectral features in speech (Mel-frequency…
With the availability of voice-enabled devices such as smart phones, mental health disorders could be detected and treated earlier, particularly post-pandemic. The current methods involve extracting features directly from audio signals. In…
Speaker verification accuracy in emotional talking environments is not high as it is in neutral ones. This work aims at accepting or rejecting the claimed speaker using his/her voice in emotional environments based on the Third-Order…
Speaker Identification process is to identify a particular vocal cord from a set of existing speakers. In the speaker identification processes, unknown speaker voice sample targets each of the existing speakers present in the system and…
A recent trend in speech processing is the use of embeddings created through machine learning models trained on a specific task with large datasets. By leveraging the knowledge already acquired, these models can be reused in new tasks where…
Speech sound disorder (SSD) refers to a type of developmental disorder in young children who encounter persistent difficulties in producing certain speech sounds at the expected age. Consonant errors are the major indicator of SSD in…
Gender recognition is an essential component of automatic speech recognition and interactive voice response systems. Determining gender of the speaker reduces the computational burden of such systems for any further processing. Typical…