Showing papers by "Tobias Bocklet published in 2021"
30 Aug 2021
TL;DR: The presented approach is based on a phonetic analysis of speech samples, thus it enabled the system to discriminate between Covid and non-Covid samples, but also to better understand how the condition influenced an individual’s speech signal.
6 citations
06 Jun 2021
TL;DR: In this article, the authors proposed the use of acoustic and linguistic methods to extract features from speech recordings and their transcriptions to discriminate people with conditions related to the Paisa mutation.
Abstract: The PSEN1-E280A or Paisa mutation is responsible for most of Early-Onset Alzheimer’s (EOA) disease cases in Colombia. It affects a large kindred of over 5000 members that present the same phenotype. The most common symptoms are related to language disorders, where speech fluency is also affected due to the difficulty to access semantic information intentionally. This study proposes the use of acoustic and linguistic methods to extract features from speech recordings and their transcriptions to discriminate people with conditions related to the Paisa mutation. We consider state-of-the-art word-embedding methods like Word2Vec and Bidirectional Encoder Representations from Transformer to process the transcripts. The speech signals are modeled by using traditional acoustic features and speaker embeddings. To the best of our knowledge, this is the first study focused on evaluating genetic Alzheimer’s and EOA using acoustics and linguistics.
4 citations