Paavo Alku

Aalto University

Finland

Research Interests

Explore related searches

Professors in Finland

Contact this professor

ORCID

Google Scholar

Academic Page

Articles (11)

Automatic Assessment of Parkinson's Disease Using Speech Representations of Phonation and Articulation

Article Link

Year:

2023

A Comparison of Data Augmentation Methods in Voice Pathology Detection

Article Link

Year:

2023

Investigation of Self-supervised Pre-trained Models for Classification of Voice Quality from Speech and Neck Surface Accelerometer Signals

Article Link

Year:

2023

Refining a Deep Learning-based Formant Tracker using Linear Prediction Methods

Article Link

Year:

2023

Analysis of Instantaneous Frequency Components of Speech Signals for Epoch Extraction

Article Link

Year:

2023

Hierarchical Multi-class Classification of Voice Disorders Using Self-supervised Models and Glottal Features

Article Link

Year:

2023

Automatic classification of the severity level of Parkinson’s disease: A comparison of speaking tasks, features, and classifiers

Article Link

Year:

2023

Exemplar-based Sparse Representations for Detection of Parkinson's Disease from Speech

Article Link

Year:

2023

Subjective Evaluation of Basic Emotions from Audio–Visual Data

Article Link

Year:

2022

End-to-end Pathological Speech Detection using Wavelet Scattering Network

Article Link

Year:

2022

Phonetic listen-and-repeat training alters 6–7-year-old children’s non-native vowel contrast production after one training session

Article Link

Year:

2022

Collaborators (5)

Tiina Ihalainen

University of Tampere

FINLAND

Saska Tirronen

Aalto University

FINLAND

Okko Räsänen

University of Tampere

FINLAND

Nelly Penttilä

University of Tampere

FINLAND

Sudarsana Reddy Kadiri

Aalto University

FINLAND

Paavo Alku

Research Interests

Explore related searches

Contact this professor

Articles (11)

Automatic Assessment of Parkinson's Disease Using Speech Representations of Phonation and Articulation

A Comparison of Data Augmentation Methods in Voice Pathology Detection

Investigation of Self-supervised Pre-trained Models for Classification of Voice Quality from Speech and Neck Surface Accelerometer Signals

Refining a Deep Learning-based Formant Tracker using Linear Prediction Methods

Analysis of Instantaneous Frequency Components of Speech Signals for Epoch Extraction

Hierarchical Multi-class Classification of Voice Disorders Using Self-supervised Models and Glottal Features

Automatic classification of the severity level of Parkinson’s disease: A comparison of speaking tasks, features, and classifiers

Exemplar-based Sparse Representations for Detection of Parkinson's Disease from Speech

Subjective Evaluation of Basic Emotions from Audio–Visual Data

End-to-end Pathological Speech Detection using Wavelet Scattering Network

Phonetic listen-and-repeat training alters 6–7-year-old children’s non-native vowel contrast production after one training session

Collaborators (5)

Tiina Ihalainen

Saska Tirronen

Okko Räsänen

Nelly Penttilä

Sudarsana Reddy Kadiri

How do I reach out?

Meet Kite AI