human
Mask-filling: Given a sequence of tables T and a question Q with [MASK], what is the word at [MASK]?
question Q： Is the proposed framework capable of inserting expressiveness into synthetic speech? shows that we obtain an MCD of [MASK] and an: Performance obtained using different features for emotion recognition and speaking style classific.
sequence of table T：
<C>Metric MCD  ,Model Setup,Dataset Reference  w / o synth . ref .  64 - dim para . enc .,<max>24.01, Base EVoCA  w / 128 - dim para . enc .  64 - dim para . enc .,10.71, Base EVoCA  w / o synth . ref .  64 - dim para . enc .,, Base EVoCA  w / o para . enc .  64 - dim para . enc .,, Base EVoCA  w / 128 - dim para . enc .  64 - dim para . enc .,, w /  64 - dim para . enc .,, w /  32 - dim para . enc .,, w / 128 - dim converter,, w /  64 - dim converter,, w /  32 - dim converter,,<C> F 0 RMSE  ( Hz ),Model Setup,Dataset Reference  w / 128 - dim para . enc .  64 - dim para . enc .,146.20, Base EVoCA  w / 128 - dim para . enc .  64 - dim para . enc .,<max>64.36, Base EVoCA  w / 128 - dim para . enc .  64 - dim para . enc .,, w /  64 - dim para . enc .,, w /  32 - dim para . enc .,, Base EVoCA  w / 128 - dim converter,, w /  64 - dim converter,, w /  32 - dim converter,,Table 1: Objective performance measures for the style voice conversion task with different setups. The base EVoCA consists of a 256-dimensional paralinguistic encoder and a 256-dimensional voice converter. Refer-ence numbers are computed using the synthetic speech and ground-truth expressive speech. All other numbers are computed using converted speech and ground-truth expressive speech.
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
Yes

--- Answer ---
grounded