This paper describes IDEA a database of Italian dysarthric speech produced by 45 speakers affected by 8 different pathologies. Neurologic diagnoses were collected from the subjects' medical records, while dysarthria assessment was conducted by a speech language pathologist and neurologist. The total number of records is 16794. The speech material consists of 211 isolated common words recorded by a single condenser microphone. The words that refer to an ambient assisted living scenario, have been selected to cover as widely as possible all Italian phonemes.The recordings, supervised by a speech pathologist, were recorded through the RECORDIA software that was developed specifically for this task. It allows multiple recording procedures depending on the patient severity and it includes an electronic record for storing patients' clinical data. All the recordings in IDEA are annotated with a TextGrid file which defines the boundaries of the speech within the wave file and other types of notes about the record.This paper also includes preliminary experiments on the recorded data to train an automatic speech recognition system from a baseline Kaldi recipe. We trained HMM and DNN models and the results shows 11.75% and 14.99% of WER respectively.

IDEA: An Italian Dysarthric Speech Database

Marini M.
Primo
;
Corbo M.;Fattori B.;D'Anna C.;Donati M.;Fanucci L.
Ultimo
2021-01-01

Abstract

This paper describes IDEA a database of Italian dysarthric speech produced by 45 speakers affected by 8 different pathologies. Neurologic diagnoses were collected from the subjects' medical records, while dysarthria assessment was conducted by a speech language pathologist and neurologist. The total number of records is 16794. The speech material consists of 211 isolated common words recorded by a single condenser microphone. The words that refer to an ambient assisted living scenario, have been selected to cover as widely as possible all Italian phonemes.The recordings, supervised by a speech pathologist, were recorded through the RECORDIA software that was developed specifically for this task. It allows multiple recording procedures depending on the patient severity and it includes an electronic record for storing patients' clinical data. All the recordings in IDEA are annotated with a TextGrid file which defines the boundaries of the speech within the wave file and other types of notes about the record.This paper also includes preliminary experiments on the recorded data to train an automatic speech recognition system from a baseline Kaldi recipe. We trained HMM and DNN models and the results shows 11.75% and 14.99% of WER respectively.
2021
978-1-7281-7066-4
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1116662
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 7
social impact