1,577 research outputs found
Forward Attention in Sequence-to-sequence Acoustic Modelling for Speech Synthesis
This paper proposes a forward attention method for the sequenceto- sequence
acoustic modeling of speech synthesis. This method is motivated by the nature
of the monotonic alignment from phone sequences to acoustic sequences. Only the
alignment paths that satisfy the monotonic condition are taken into
consideration at each decoder timestep. The modified attention probabilities at
each timestep are computed recursively using a forward algorithm. A transition
agent for forward attention is further proposed, which helps the attention
mechanism to make decisions whether to move forward or stay at each decoder
timestep. Experimental results show that the proposed forward attention method
achieves faster convergence speed and higher stability than the baseline
attention method. Besides, the method of forward attention with transition
agent can also help improve the naturalness of synthetic speech and control the
speed of synthetic speech effectively.Comment: 5 pages, 3 figures, 2 tables. Published in IEEE International
Conference on Acoustics, Speech and Signal Processing 2018 (ICASSP2018
How to interpret a discovery or null result of the decay
The Majorana nature of massive neutrinos will be crucially probed in the
next-generation experiments of the neutrinoless double-beta ()
decay. The effective mass term of this process, , may
be contaminated by new physics. So how to interpret a discovery or null result
of the decay in the foreseeable future is highly nontrivial. In
this paper we introduce a novel three-dimensional description of , which allows us to see its sensitivity to the lightest
neutrino mass and two Majorana phases in a transparent way. We take a look at
to what extent the free parameters of can be well
constrained provided a signal of the decay is observed someday.
To fully explore lepton number violation, all the six effective Majorana mass
terms (for )
are calculated and their lower bounds are illustrated with the two-dimensional
contour figures. The effect of possible new physics on the decay
is also discussed in a model-independent way. We find that the result of
in the normal (or inverted) neutrino mass ordering
case modified by the new physics effect may somewhat mimic that in the inverted
(or normal) mass ordering case in the standard three-flavor scheme. Hence a
proper interpretation of a discovery or null result of the decay
may demand extra information from some other measurements.Comment: 13 pages, 6 figures, Figures and references update
Neural Speech Phase Prediction based on Parallel Estimation Architecture and Anti-Wrapping Losses
This paper presents a novel speech phase prediction model which predicts
wrapped phase spectra directly from amplitude spectra by neural networks. The
proposed model is a cascade of a residual convolutional network and a parallel
estimation architecture. The parallel estimation architecture is composed of
two parallel linear convolutional layers and a phase calculation formula,
imitating the process of calculating the phase spectra from the real and
imaginary parts of complex spectra and strictly restricting the predicted phase
values to the principal value interval. To avoid the error expansion issue
caused by phase wrapping, we design anti-wrapping training losses defined
between the predicted wrapped phase spectra and natural ones by activating the
instantaneous phase error, group delay error and instantaneous angular
frequency error using an anti-wrapping function. Experimental results show that
our proposed neural speech phase prediction model outperforms the iterative
Griffin-Lim algorithm and other neural network-based method, in terms of both
reconstructed speech quality and generation speed.Comment: Accepted by ICASSP 2023. Codes are availabl
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