Automated Cross-language Intelligibility Analysis of Parkinson's Disease Patients Using Speech Recognition Technologies

no code implementations • ACL 2019 • Nina Hosseini-Kivanani, Juan Camilo V{\'a}squez-Correa, Manfred Stede, Elmar N{\"o}th

In the present study, we plan to analyze the speech signals of PD patients and healthy control (HC) subjects in three different languages: German, Spanish, and Czech, with the aim to identify biomarkers to discriminate between PD patients and HC subjects and to evaluate the neurological state of the patients.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Assessing the Prosody of Non-Native Speakers of English: Measures and Feature Sets

no code implementations • LREC 2016 • Eduardo Coutinho, Florian H{\"o}nig, Yue Zhang, Simone Hantke, Anton Batliner, Elmar N{\"o}th, Bj{\"o}rn Schuller

We also discuss the impact of various fusion strategies on performance. Overall, our results demonstrate that the prosody of non-native speakers of English as L2 can be reliably assessed using supra-segmental audio features; prosodic features seem to be the most important ones.

regression

New Spanish speech corpus database for the analysis of people suffering from Parkinson's disease

no code implementations • LREC 2014 • Juan Rafael Orozco-Arroyave, Juli{\'a}n David Arias-Londo{\~n}o, Jes{\'u}s Francisco Vargas-Bonilla, Mar{\'\i}a Claudia Gonz{\'a}lez-R{\'a}tiva, Elmar N{\"o}th

Different researchers are currently working in the analysis of speech of people with PD, including the study of different dimensions in speech such as phonation, articulation, prosody and intelligibility.

Erlangen-CLP: A Large Annotated Corpus of Speech from Children with Cleft Lip and Palate

no code implementations • LREC 2014 • Tobias Bocklet, Andreas Maier, Korbinian Riedhammer, Ulrich Eysholdt, Elmar N{\"o}th

In this paper we describe Erlangen-CLP, a large speech database of children with Cleft Lip and Palate.