Projects per year
Synthetic speech can be modified to improve intelligibility in noise. In order to perform modifications automatically, it would be useful to have an objective measure that could predict the intelligibility of modified synthetic speech for human listeners. We analysed the impact on intelligibility - and on how well objective measures predict it -“ when we separately modify speaking rate, fundamental frequency, line spectral pairs and spectral peaks. Shifting LSPs can increase intelligibility for human listeners; other modifications had weaker effects. Among the objective measures we evaluated, the Dau model and the Glimpse proportion were the best predictors of human performance.
|Title of host publication||Interspeech 2011|
|Subtitle of host publication||12th Annual Conference of the International Speech Communication Association|
|Publisher||International Speech Communication Association|
|Number of pages||4|
|Publication status||Published - 1 Aug 2011|
FingerprintDive into the research topics of 'Can Objective Measures Predict the Intelligibility of Modified HMM-based Synthetic Speech in Noise?'. Together they form a unique fingerprint.
- 2 Finished
LISTA: LISTA- The Listening Talker (RTGS)
King, S., Mayo, C. & Renals, S.
1/05/10 → 30/04/13
SCALE: Speech Communication with Adaptive Learning
1/01/09 → 31/12/12