A scheme of syllable duration prediction and F0-contour generation to synthesize Chinese speech

2003 ◽  
Author(s):  
Wei Feng ◽  
Yunbiao Xu ◽  
Li Zhao ◽  
Y. Niimi
Keyword(s):  
Syllable Duration ◽  
F0 Contour ◽  
Duration Prediction

Effects of Fundamental Frequency Contours on Sentence Recognition in Mandarin-Speaking Children With Cochlear Implants

2020 ◽  
Vol 63 (11) ◽  
pp. 3855-3864
Author(s):  
Wanting Huang ◽  
Lena L. N. Wong ◽  
Fei Chen ◽  
Haihong Liu ◽  
Wei Liang
Keyword(s):  
Cochlear Implants ◽  
Fundamental Frequency ◽  
Signal To Noise Ratio ◽  
Lexical Tone ◽  
Signal To Noise ◽  
Sentence Recognition ◽  
Test Conditions ◽  
Age Appropriate ◽  
F0 Contour ◽  
Appropriate Sentences

Purpose Fundamental frequency (F0) is the primary acoustic cue for lexical tone perception in tonal languages but is processed in a limited way in cochlear implant (CI) systems. The aim of this study was to evaluate the importance of F0 contours in sentence recognition in Mandarin-speaking children with CIs and find out whether it is similar to/different from that in age-matched normal-hearing (NH) peers. Method Age-appropriate sentences, with F0 contours manipulated to be either natural or flattened, were randomly presented to preschool children with CIs and their age-matched peers with NH under three test conditions: in quiet, in white noise, and with competing sentences at 0 dB signal-to-noise ratio. Results The neutralization of F0 contours resulted in a significant reduction in sentence recognition. While this was seen only in noise conditions among NH children, it was observed throughout all test conditions among children with CIs. Moreover, the F0 contour-induced accuracy reduction ratios (i.e., the reduction in sentence recognition resulting from the neutralization of F0 contours compared to the normal F0 condition) were significantly greater in children with CIs than in NH children in all test conditions. Conclusions F0 contours play a major role in sentence recognition in both quiet and noise among pediatric implantees, and the contribution of the F0 contour is even more salient than that in age-matched NH children. These results also suggest that there may be differences between children with CIs and NH children in how F0 contours are processed.

An F0 contour control model using an F0 contour codebook

2007 ◽  
Vol 38 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Takehiko Kagoshima ◽  
Masahiro Morita ◽  
Shigenobu Seto ◽  
Masami Akamine ◽  
Yoshinori Shiga
Keyword(s):  
Control Model ◽  
Contour Control ◽  
F0 Contour

Multiple f0 contour parallel Viterbi search for unit selection speech synthesis

2011 ◽  
Vol 47 (16) ◽  
pp. 937 ◽  
Author(s):  
F. Campillo ◽  
E.R. Banga
Keyword(s):  
Speech Synthesis ◽  
Unit Selection ◽  
F0 Contour ◽  
Viterbi Search

Duration prediction of Chilean strong motion data using machine learning

2021 ◽  
Vol 109 ◽  
pp. 103253
Author(s):  
Sarit Chanda ◽  
M.C. Raghucharan ◽  
K.S.K. Karthik Reddy ◽  
Vasudeo Chaudhari ◽  
Surendra Nadh Somala
Keyword(s):  
Machine Learning ◽  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data ◽  
Duration Prediction

Traffic Incident Duration Prediction using BERT Representation of Text

2021 ◽  
Author(s):  
Prashansa Agrawal ◽  
Antony Franklin ◽  
Digvijay Pawar ◽  
Srijith PK
Keyword(s):  
Traffic Incident ◽  
Incident Duration ◽  
Duration Prediction
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