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Person

Shahin Amiriparian

Wissenschaftlicher Mitarbeiter

Name	Shahin Amiriparian
Zeit	ca. 20./21. Jh. (Lebensdaten)
Ort	Deutschland
Geschlecht	männlich
Akademischer Grad bzw. Titel	M.Sc.
Beruf	Wissenschaftlicher Mitarbeiter (charakteristischer Beruf)
Beziehung	Informationstechnik (Studienfach) Medizinische Informatik (Thema)
Themengebiet	Personen zu Informatik, Datenverarbeitung Personen zu Medizin, Tiermedizin
Weitere Angaben	Wiss. Mitarbeiter an der Universität Augsburg, ZD.B Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing (Stand 11/19)
Quelle	https://www.informatik.uni-augsburg.de/de/lehrstuehle/eihw/staff/amiriparian/ (Stand: 13.11.2019)
Datensatztyp	Person
GND-Nummer	1199452319
Datensatz-ID	1199452319
Beteiligt an alle anzeigen COLD Fusion: calibrated and ordinal latent distribution fusion for uncertainty-aware multimodal emotion recognition Validation of machine learning-based assessment of major depressive disorder from paralinguistic speech characteristics in routine care Validation of Machine Learning‐Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care A summary of the ComParE COVID-19 challenges Computational charisma: a brick by brick blueprint for building charismatic artificial intelligence Guest editorial: special issue on affective speech and language synthesis, generation, and conversion HEAR4Health: a blueprint for making computer audition a staple of modern healthcare The ACM Multimedia 2023 Computational Paralinguistics Challenge: emotion share & requests Zero-shot personalization of speech foundation models for depressed mood monitoring A summary of the ComParE COVID-19 challenges DeepSpectrumLite: a power-efficient transfer learning framework for embedded speech and audio processing from decentralised data Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease Face mask recognition from audio: the MASC database and an overview on the mask challenge motilitAI: a machine learning framework for automatic prediction of human sperm motility The ACM Multimedia 2022 Computational Paralinguistics Challenge: vocalisations, stuttering, activity, & mosquitoes The influence of pleasant and unpleasant odours on the acoustics of speech New avenues in audio intelligence: towards holistic real-life audio understanding The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 cough, COVID-19 speech, escalation & primates The voice of COVID-19: acoustic correlates of infection in sustained vowels "Are you playing a shooter again?!": Deep representation learning for audio-based video game genre recognition Deep attentive end-to-end continuous breath sensing from speech Emotion and themes recognition in music with convolutional and recurrent attention-blocks Group-level speech emotion recognition utilising deep spectrum features The INTERSPEECH 2020 Computational Paralinguistics Challenge: elderly emotion, breathing & masks Toward silent paralinguistics: speech-to-EMG — retrieving articulatory muscle activity from speech Towards silent paralinguistics: deriving speaking mode and speaker ID from electromyographic signals Unsupervised representation learning with attention and sequence to sequence autoencoders to predict sleepiness from speech Audio-based eating analysis and tracking utilising deep spectrum features Audio-based recognition of bipolar disorder utilising capsule networks AVEC 2019 workshop and challenge: state-of-mind, detecting depression with AI, and cross-cultural affect recognition Can deep generative audio be emotional? Towards an approach for personalised emotional audio generation Emotion and themes recognition in music utilising convolutional and recurrent neural networks Predicting biological signals from speech: introducing a novel multimodal dataset and results Synchronization in interpersonal speech The INTERSPEECH 2019 computational paralinguistics challenge: Styrian dialects, continuous sleepiness, baby sounds & orca activity Using speech to predict sequentially measured cortisol levels during a trier social stress test A fusion of deep convolutional generative adversarial networks and sequence to sequence autoencoders for acoustic scene classification AVEC 2018 workshop and challenge: bipolar disorder and cross-cultural affect recognition Bag-of-deep-features: noise-robust deep feature representations for audio analysis Deep convolutional recurrent neural network for rare acoustic event detection Deep unsupervised representation learning for abnormal heart sound classification Low level texture features for snore sound discrimination Multimodal bag-of-words for cross domains sentiment analysis Recognition of echolalic autistic child vocalisations utilising convolutional recurrent neural networks The INTERSPEECH 2018 computational paralinguistics challenge: atypical and self-assessed affect, crying and heart beats "You sound ill, take the day off": automatic recognition of speech affected by upper respiratory tract infection An 'end-to-evolution' hybrid approach for snore sound classification An image-based deep spectrum feature representation for the recognition of emotional speech Automatic classification of autistic child vocalisations: a novel database and results CAST a database: rapid targeted large-scale big data acquisition via small-world modelling of social media platforms Feature selection in multimodal continuous emotion prediction Sentiment analysis using image-based deep spectrum features Snore sound classification using image-based deep spectrum features The combined Augsburg / Passau / TUM / ICL system for DCASE 2017 Is deception emotional? An emotion-driven predictive approach Emotion recognition in the wild: incorporating voice and lip activity in multimodal decision-level fusion

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Katalog der Deutschen Nationalbibliothek

Shahin Amiriparian

COLD Fusion: calibrated and ordinal latent distribution fusion for uncertainty-aware multimodal emotion recognition

Validation of machine learning-based assessment of major depressive disorder from paralinguistic speech characteristics in routine care

Validation of Machine Learning‐Based Assessment of Major Depressive Disorder from Paralinguistic Speech Characteristics in Routine Care

A summary of the ComParE COVID-19 challenges

Computational charisma: a brick by brick blueprint for building charismatic artificial intelligence

Guest editorial: special issue on affective speech and language synthesis, generation, and conversion

HEAR4Health: a blueprint for making computer audition a staple of modern healthcare

The ACM Multimedia 2023 Computational Paralinguistics Challenge: emotion share & requests

Zero-shot personalization of speech foundation models for depressed mood monitoring

A summary of the ComParE COVID-19 challenges

DeepSpectrumLite: a power-efficient transfer learning framework for embedded speech and audio processing from decentralised data

Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease

Face mask recognition from audio: the MASC database and an overview on the mask challenge

motilitAI: a machine learning framework for automatic prediction of human sperm motility

The ACM Multimedia 2022 Computational Paralinguistics Challenge: vocalisations, stuttering, activity, & mosquitoes

The influence of pleasant and unpleasant odours on the acoustics of speech

New avenues in audio intelligence: towards holistic real-life audio understanding

The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 cough, COVID-19 speech, escalation & primates

The voice of COVID-19: acoustic correlates of infection in sustained vowels

"Are you playing a shooter again?!": Deep representation learning for audio-based video game genre recognition

Deep attentive end-to-end continuous breath sensing from speech

Emotion and themes recognition in music with convolutional and recurrent attention-blocks

Group-level speech emotion recognition utilising deep spectrum features

The INTERSPEECH 2020 Computational Paralinguistics Challenge: elderly emotion, breathing & masks

Toward silent paralinguistics: speech-to-EMG — retrieving articulatory muscle activity from speech

Towards silent paralinguistics: deriving speaking mode and speaker ID from electromyographic signals

Unsupervised representation learning with attention and sequence to sequence autoencoders to predict sleepiness from speech

Audio-based eating analysis and tracking utilising deep spectrum features

Audio-based recognition of bipolar disorder utilising capsule networks

AVEC 2019 workshop and challenge: state-of-mind, detecting depression with AI, and cross-cultural affect recognition

Can deep generative audio be emotional? Towards an approach for personalised emotional audio generation

Emotion and themes recognition in music utilising convolutional and recurrent neural networks

Predicting biological signals from speech: introducing a novel multimodal dataset and results

Synchronization in interpersonal speech

The INTERSPEECH 2019 computational paralinguistics challenge: Styrian dialects, continuous sleepiness, baby sounds & orca activity

Using speech to predict sequentially measured cortisol levels during a trier social stress test

A fusion of deep convolutional generative adversarial networks and sequence to sequence autoencoders for acoustic scene classification

AVEC 2018 workshop and challenge: bipolar disorder and cross-cultural affect recognition

Bag-of-deep-features: noise-robust deep feature representations for audio analysis

Deep convolutional recurrent neural network for rare acoustic event detection

Deep unsupervised representation learning for abnormal heart sound classification

Low level texture features for snore sound discrimination

Multimodal bag-of-words for cross domains sentiment analysis

Recognition of echolalic autistic child vocalisations utilising convolutional recurrent neural networks

The INTERSPEECH 2018 computational paralinguistics challenge: atypical and self-assessed affect, crying and heart beats

"You sound ill, take the day off": automatic recognition of speech affected by upper respiratory tract infection

An 'end-to-evolution' hybrid approach for snore sound classification

An image-based deep spectrum feature representation for the recognition of emotional speech

Automatic classification of autistic child vocalisations: a novel database and results

CAST a database: rapid targeted large-scale big data acquisition via small-world modelling of social media platforms

Feature selection in multimodal continuous emotion prediction

Sentiment analysis using image-based deep spectrum features

Snore sound classification using image-based deep spectrum features

The combined Augsburg / Passau / TUM / ICL system for DCASE 2017

Is deception emotional? An emotion-driven predictive approach

Emotion recognition in the wild: incorporating voice and lip activity in multimodal decision-level fusion