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Paavo Alku

Aalto University

Finland

Research Interests

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Articles (23)

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Collaborators (14)

Tiina Ihalainen

university lecturer

University of Tampere

FINLAND

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Topi Rönkkö

University of Tampere

FINLAND

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Saska Tirronen

Aalto University

FINLAND

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Shrikanth Narayanan

University Professor and Niki & Max Nikias Chair in Engineering and Professor

University of Southern California

UNITED STATES

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Dani Byrd

Professor

University of Southern California

UNITED STATES

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Sampo Saari

Senior Lecturer (D.Sc.)

University of Tampere

FINLAND

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Okko Räsänen

Associate professor

University of Tampere

FINLAND

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Sneha Das

Assistant Professor

Technical University of Denmark

DENMARK

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Nelly Penttilä

University lecturer

University of Tampere

FINLAND

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Lotta-Maria Oksanen

University of Helsinki

FINLAND

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Ahmed Geneid

Adj. Professor

Helsinki University Hospital

FINLAND

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Sudarsana Reddy Kadiri

Research Assistant Professor

University of Southern California

UNITED STATES

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Paavo Heikkilä

University of Tampere

FINLAND

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Mari Leppävuori

Senior Lecturer, Music Pedagogy

University of Tampere

FINLAND

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Paavo Alku

Research Interests

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Articles (23)

Classification of Phonation types in Singing and Speaking Voice Using Self-Supervised Learning Models

Glottal Inverse Filtering and Its Application in the Automatic Classification of Diseases from Speech

"Metal" and "Density" in Phonation According to Complete Vocal Technique: Double-Case Study with Special Reference to Vocal Efficiency and Economy

Effects of Spoken Phones and Patient Characteristics on Respiratory Aerosol Emission

Automatic Classification of Strain in the Singing Voice Using Machine Learning

Towards robust heart failure detection in digital telephony environments by utilizing transformer-based codec inversion

Formant Tracking by Combining Deep Neural Network and Linear Prediction

Automatic classification of vocal intensity categories from amplitude-normalized speech signals by comparing acoustic features and classifier models

Automatic Detection of Parkinsonian Speech using Wavelet Scattering Features

Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features

The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals

Wavelet scattering network features for intensity category classification and prediction of SPL from speech

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 (14)

Tiina Ihalainen

Topi Rönkkö

Saska Tirronen

Shrikanth Narayanan

Dani Byrd

Sampo Saari

Okko Räsänen

Sneha Das

Nelly Penttilä

Lotta-Maria Oksanen

Ahmed Geneid

Sudarsana Reddy Kadiri

Paavo Heikkilä

Mari Leppävuori

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