Publication

Novel Methods For Detection And Analysis Of Atypical Aspects In Speech

Publications associées (146)

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Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...

Idiap2020

Dysarthric Speech Recognition with Lattice-Free MMI

Enno Hermann

Recognising dysarthric speech is a challenging problem as it differs in many aspects from typical speech, such as speaking rate and pronunciation. In the literature the focus so far has largely been on handling these variabilities in the framework of HMM/G ...

2020

End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition

Ronan Collobert, Dimitri Palaz

In hidden Markov model (HMM) based automatic speech recognition (ASR) system, modeling the statistical relationship between the acoustic speech signal and the HMM states that represent linguistically motivated subword units such as phonemes is a crucial st ...

ELSEVIER SCIENCE BV2019

Spectral Subspace Analysis for Automatic Assessment of Pathological Speech Intelligibility

Hervé Bourlard, Ina Kodrasi, Parvaneh Janbakhshi

Speech intelligibility is an important assessment criterion of the communicative performance of pathological speakers. To assist clinicians in their assessment, time- and cost-efficient automatic intelligibility measures offering a repeatable and reliable ...

2019

The recent increase in social media based propaganda, i.e., ‘fake news’, calls for automated methods to detect tampered content. In this paper, we focus on detecting tampering in a video with a person speaking to a camera. This form of manipulation is easy ...

2019

Improving Children Speech Recognition through Feature Learning from Raw Speech Signal

Selen Hande Kabil, Subrahmanya Pavankumar Dubagunta

Children speech recognition based on short-term spectral features is a challenging task. One of the reasons is that children speech has high fundamental frequency that is comparable to formant frequency values. Furthermore, as children grow, their vocal ap ...

IEEE2019

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Impaired speech intelligibility in motor speech disorders arising due to neurological diseases negatively affects the communication ability and quality of life of patients. Reliable and cost-effective measures to automatically assess speec ...

2019

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IEEE2019

The goal of this thesis is to improve current state-of-the-art techniques in speaker verification (SV), typically based on âidentity-vectorsâ (i-vectors) and deep neural network (DNN), by exploiting diverse (phonetic) information extracted using variou ...

EPFL2018

On Learning Vocal Tract System Related Speaker Discriminative Information from Raw Signal Using CNNs

Sébastien Marcel, Hannah Muckenhirn

In a recent work, we have shown that speaker verification systems can be built where both features and classifiers are directly learned from the raw speech signal with convolutional neural networks (CNNs). In this framework, the training phase also decides ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

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